The Effect of Viewing Posts in Online Brand Communities

15
Department of Marketing, College of Management, Shenzhen University Prof. Dr. Zhimin Zhou [email protected] Are Visitors Outsiders? The Effect of Viewing Posts in Online Brand Communities Zhimin Zhou Shenzhen University, China Ning Zhang City University of Hong Kong, Hong Kong S.A.R.

Transcript of The Effect of Viewing Posts in Online Brand Communities

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Are Visitors Outsiders?

The Effect of Viewing Posts in

Online Brand Communities

Zhimin Zhou

Shenzhen University, China

Ning Zhang

City University of Hong Kong, Hong Kong S.A.R.

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

83,415 Online Users at a point in time:5,324 members

and 78,091 visitors

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

How can influence visitors be influenced by

online brand communities to participate in the

communities and purchase the brands?

Research Questions

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Conceptual Model

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Measures

●Viewing posts (Bateman, Gray, and Butler, 2010; Koh and Kim,

2004): three items

●Informational value (Mathwick, Wiertz, and de Ruyter, 2008): three

items

●Perceived social value (Mathwick, Wiertz, and de Ruyter, 2008): four

items

●Attitude toward community (Gupta, Kim, and Shin, 2010): four items

●Attitude toward brand (Putrevu and Lord, 1994): five items

●Participation intention (Algesheimer, Dholakia, and Herrmann, 2005;

Bagozzi and Dholakia, 2006): three items

●Purchase intention (Putrevu and Lord, 1994): three items.

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Data Collection and Analysis Method

●Data Collection

●The website Sojump (www.sojump.com), a popular online

survey platform in China

●376 valid questionnaires

●Analysis Method

●Partial least square (PLS) modeling

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Sampling

Gender Age Income(RMB) Vocation Education

Male 48.1%

Female 51.9%

≤20 12.5%

21-25 41.2%

26-30 24.5%

31-40 17.8%

41-50 2.7%

≥51 1.3%

No income 26.9%

< 2000 16.2%

2000-3000 21.0%

3001-5000 20.2%

5001-8000 11.2%

8001-15000 2.9%

15001-50000 1.6%

Student 33.5%

Non-student (such as sales, engineer, worker, teacher)

66.5%

Primary school 1.1%

High school 5.3%

Secondary technical school 2.9%

Junior college 18.9%

Undergraduate 61.4%

Post-graduate 9.6%

Doctorate 0.8%

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Measurement Model SFL t-value

Viewing posts (Cronbach’s α = .834)

I have viewed posts in OBC X for a long time. .843 40.380

I have visited OBC X to view posts frequently. .902 67.923

I have viewed a large number of posts presented by members in OBC X. .854 41.800

Informational value (Cronbach’s α = .816)

I find the information on OBC X to be valuable. .891 66.168

I think of OBC X as an information resource. .866 49.700

There is unique value in OBC X. .802 25.150

Perceived social value (Cronbach’s α = .829)

I feel that members think of the patrons of OBC X as members’ extended

family.

.813 31.567

I feel that participating on OBC X provides an important source of

camaraderie for members.

.858 47.050

I feel that OBC X provides a sounding board for members’ ideas. .760 22.842

I feel that members rely on the personal support they get from others in

OBC X.

.819 42.188

Attitude toward community (Cronbach’s α = .897)

OBC X is a good online forum. .903 77.354

OBC X is a likeable online forum. .883 50.581

OBC X is a beneficial online forum. .841 44.184

OBC X is a pleasant online forum. .868 49.142

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Cont’d

SFL t-value

Attitude toward brand (Cronbach’s α = .905)

The decision to buy Brand X is foolish.(r) .664* 14.627

Buying Brand X is a good decision. .905 60.526

I think Brand X is a satisfactory brand. .917 82.934

I think Brand X has a lot of beneficial characteristics. .886 49.415

I have a favorable opinion of Brand X. .875 57.940

Participation intention (Cronbach’s α = .884)

I intend to be a part of OBC X. .912 63.942

I intend to participate in the activities of OBC X. .917 76.547

I intend to communicate with members of OBC X. .875 39.599

Purchase intention (Cronbach’s α = .881)

It is very likely that I will buy Brand X. .902 44.135

I will purchase Brand X the next time I need the product. .933 110.670

I will definitely try Brand X. .861 38.933

Overall model fit: χ2(263)= 732.53, χ2/df=2.79, p<.01; CFI=.93; NNFI=.92; IFI=.93;

RMSEA=.070

* For the loadings of reverse questions, the response data are subtracted by 7.

Notes: OBC X means online community of brand X. (r) indicates a reverse question. SFL means standardized factor

loadings.

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Descriptive Statistics of Construct Measures

Variables 1 2 3 4 5 6 7

1. Viewing posts .87**

2. Informational value .39** .85**

3. Perceived social value .46** .53** .81**

4. Attitude toward community .50** .56** .69** .87**

5. Attitude toward brand .32** .50** .44** .53** .85**

6. Participation intention .48** .52** .64** .69** .42** .90**

7. Purchase intention .35** .45** .36** .50** .71** .39** .90**

Mean 4.07 4.58 4.23 4.36 4.60 4.38 4.71

Standard deviation 1.08 .89 .88 .88 .84 .95 .96

Composite reliability .90 .89 .89 .93 .93 .93 .93

AVE .75 .73 .66 .76 .73 .81 .81** p < .01 (two-tailed test).

Notes: Bold figures on the diagonal are the square root of the AVE for the

constructs.

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

* p < .05 (two-tailed test); ** p < .01 (two-tailed test).

Hypothesized Paths Coefficient t-value Results

Main effects

H1a: viewing posts → informational value .400** 7.202 supported

H1b: viewing posts → perceived social value .457** 8.431 supported

H2a: informational value → attitude toward community .271** 4.940 supported

H2b: informational value → attitude toward brand .294** 4.748 supported

H3a: perceived social value → attitude toward community .549** 13.416 supported

H3b: perceived social value → attitude toward brand .060 1.061 rejected

H4: attitude toward community → attitude toward brand .324** 3.735 supported

H5a: attitude toward community → participation intention .652** 12.538 supported

H5b: attitude toward community → purchase intention .151* 2.463 supported

H6a: attitude toward brand → participation intention .070 1.458 rejected

H6b: attitude toward brand → purchase intention .632** 10.194 supported

H7: participation intention → purchase intention .002 0.057 rejected

Tests of Hypotheses

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Control effects Coefficient t-value

Gender → purchase intention .004 .181

Age → purchase intention -.005 .127

Income → purchase intention .073 1.554

Education → purchase intention .036 1.275

Dependent variables Overall R2

informational value .160

perceived social value .209

attitude toward community .536

attitude toward brand .349

participation intention .486

purchase intention .541

Cont’d

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Research Conclusions

×

××

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Managerial Implications

●facilitating online information sharing

●foster a culture of harmony

●promote members’ interactions

Department of Marketing, College of Management, Shenzhen

UniversityProf. Dr. Zhimin Zhou [email protected]

Limitations and Future Research

●common method bias

●variation of the model among different industries

●dynamic mechanism from visitors to members