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An Empirical Study of Social Network Attachment and Its Role in Community Cohesiveness

Master Thesis
by

Mark Salvacion

on 14 November 2015

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Transcript of An Empirical Study of Social Network Attachment and Its Role in Community Cohesiveness

Conclusion

The Research Model

Social Network Attachment
Social Network Identity
Social Network Prominence
Social Network Dependence
Community Involvement
Community Cohesiveness
The Attachment Theory
Social Psychology
For example:
Mother-infant relationship (Bowlby 1969/1982)

Adult romantic relationship (Hazan and Shaver 1987)
Consumer Behavior
For example:
Individual-object connection (Wallendorf and Arnould 1988)

Product-brand relationships (Park et al. 2010)
Information Systems
For example:
Product or Service Attachment (Choi 2013)
Social Network Anxiety
An emotion that a member feels when the online social network will not be available in times when he or she needs it.
When a member perceives symbolic importance and feels “a sense of oneness” with his or her preferred online social network.
I feel that this social network site is a part of me.
I identify with this social network site.
This social network site means a lot more to me than other sites.
When thoughts and feelings about the online social network become part of memory and occur to mind automatically.
Thoughts and feelings about this social network site are automatic, and come to my mind seemingly on their own.
This social network site brings me positive thoughts and feelings.
Thoughts and feelings toward this social network site come to my mind naturally and instantly.
When a member becomes reliant on the attributes that provide support to their personal goals and desired activities.
Few other websites can compare to this social network site.
I get more satisfaction from visiting this social network site than visiting other sites.
Using this social network site is one of the best things I do.
I wouldn't substitute any other site for doing the types of things I do at this social network site.
Doing what I do on this social network site is more important to me than doing it on any other sites.
I worry about losing access to this social network site.
My life without this social network site is unimaginable.
If I have no access to this social network site, I feel very anxious and distressed.
The passive and active form of behavior whereby an individual is engaged or participating in an online activity.
I use this social network site to share or receive stories or take part in conversations.
I use this social network site to observe/learn more about some things.
I find this social network site as a good place to express myself.
When the online social network portrays harmony as a result of the community member’s good moral and commitment.
I feel that I am a member of this social network site.
Many of the members in this social network site help each other.
Most members in this social network site get along together.
Research Questions:
(1) Underlying factors of Attachment?
(2) Role in Community Cohesiveness?
An Empirical Analysis of
Social Network Attachment
and Its Role in Community Cohesiveness

Mark Mikhail Salvacion
October 28, 2015

Data Collection
Online Survey -

http://tiny.cc/shortsurvey
February 05th - March 30th, 2015
Valid
Invalid
235
509
Total = 744 Participants
= 47%
= 53%
Descriptive Statistics
Which country are you from?
Most commonly used Social network site
Most often used on a mobile device.
(e.g., laptop, smartphone or tablet)
How long have you been using this social network site?
Average time the respondents spend on this social network site.
How many contacts / friends do you have who are on this social network site?
What information do you include on your social network profile?
Do you usually add / accept strangers who wants to be your friend on this social network site?
The most common reasons for using this social network site:
Demographic
SNS Usage
Data Analysis Methodology
Partial Least Squares Structural Equation Modeling (PLS-SEM)
Primarily used to develop theories in exploratory research.

Goal is to predict key target constructs or to identify key "driver" constructs.

Focuses on explaining the variance in the dependent variables.
Evaluation of the (Reflective) Measurement Models
Evaluation of the Structural
Models
Individual Indicator Reliability
Outer-loadings
Internal Consistency
Composite Reliability


Convergent Validity
Average Variance Extracted (AVE)
Discriminant Validity
Cross-loadings
Fornell-Larcker (√AVE)
Collinearity Issue Assessment
Variance Inflation Factor (VIF)
Significance of Path Coefficients
Bootstrapping technique
Relevance of relationships
Total Effects
Coefficient of Determination
R-square value (R2)
Effect Size
F-square value (f2)
Predictive Relevance
Blindfolding technique (Q2)

Systematic Evaluation in PLS-SEM
Partial Least Squares Multi-Group Analysis
(PLS-MGA)
Individual Indicator Reliability
Rule of Thumb:
Internal Consistency
Rule of Thumb:
Convergent Validity
Rule of Thumb:
Measurement Model Evaluation
Outer loadings
each item has to be 0.708 or higher since that number squared is equivalent to 0.50.
Cronbach’s alpha
sensitive and is easily affected by the number of items in a scale.
Composite Reliability
less sensitive and not easily affected
treated the same way as Cronbach's alpha
values between 0.70 and 0.90 can be regarded as satisfactory.
Average Variance Extracted (AVE)
value 0.50 or higher indicates that, on average, the construct explains more than half of the variance of its indicators.
Discriminant Validity
Rule of Thumb:
Cross-loadings
item's outer loading value on their associated construct has to be higher than on other constructs.

Fornell-Larcker method
Square root of the AVE must be greater than the correlations of constructs with other latent variables.
Rule of Thumb:
Evaluation of the Structural Models
Collinearity Issue Assessment
Rule of Thumb:
Significance of Path Coefficients
Bootstrapping Procedure
Coefficient of Determination
F-SQUARE VALUE (f2)
Value Effect Size
Indicates how much a predictor 0.02 = small
construct contributes on the R2 0.15 = medium
value of a target construct. 0.35 = large

Effect Size
Rule of Thumb:
Predictive Relevance
Blindfolding Technique (Q2):
No sign changes, for 509 cases, and 5,000 re-samples
Note:
T Statistics > 1.96 is significant with a two-tailed test, and > 0.98 is significant for a one-tailed test for a significance level of 5% (a= 0.05).
P Values < 0.05 or > 0.95 is significant with a two-tailed test.
H4b
H2a
Relevance of Relationships
Path coefficient
Values close to +1 mean there is a strong positive relationship.

Negative value close to -1 denotes a strong negative relationship.

Values extremely close to 0 are considered non-significant.
Bootstrapping Options:
Variance inflation factor (VIF)
must be lower than 5 (5 or higher indicates a potential collinearity problem)
Results:
Total Effects
Community Involvement (0.463)
has the most impact on Community Cohesiveness.
Among the 3 primary driver (predictor) constructs
The perceived Social Network Identity (0.189) has the strongest total effect on CCO, followed by dependence (0.158), and then prominence (0.086).
H1a
H1b
H2a
H2b
H3a
H3b
H4a
H5
H4b
R-square value (R2):
H1a H1b
H2a
H2b H3a H3b H4a
H4b
H5
The proposed structural equation model explains:
38.8%
of the variance in Social Network Attachment
32.2%
of the variance in Community Involvement
31.3%
of the variance in Community Cohesiveness
Construct Cross-validated Redundancy
The results of 0.02, 0.15, and 0.35 are interpreted as small, medium, and large predictive relevance power.
Partial Least Squares Multi-Group Analysis (PLS-MGA)
Gender
H2a
&
H2b
Thoughts and feelings about the social network site does not have a significant impact on attachment and involvement.
H4b
No significant relationship between social network attachment and the passive and active form of behavior in the community.
H1b
Social network identity does not play an important role in community involvement.
H2a
Thoughts and feelings about the social network site have no crucial effect on attachment.
H4b
No significant relationship between social network attachment and community involvement.
M
F
H1b (0.439)
SNI and CIN have a positive and strong relationship.
H2a
(-0.061
)
SNP have a negative but very weak influence over SNA.
H1b
(0.150)
SNI have a positive but very weak influence over CIN.
H2a
(0.113
)
SNP have a positive but very weak influence over SNA.
Partial Least Squares Multi-Group Analysis (PLS-MGA)
Age
238 Male
271 Female
Age 18 or below =
40
records
Age 19-25 years old = 163 records
Age 26-35 years old = 173 records
Age 36 or above = 133 records
The 10 Times Rule (PLS-MGA)
The minimum number of observations per group should be equal to the maximum number of arrows pointing at a latent variable multiplied by 10.
4 x 10 = 40
Empirical Analysis
H1b
Social network identity does not play an important role in community involvement.
H2a
Thoughts and feelings about the social network site have no crucial effect on attachment.
H4b
No significant relationship between social network attachment and community involvement.
Research Findings:
(1) Underlying factors of Attachment?
H1a: Social network Identity (0.315)
H2a
: Social network Prominence (
0.039
)
H3a: Social network Dependence (0.329)

(2) Role in Online Community Cohesiveness?
H4a: There is a mild positive relationship (0.196)
Importance-Performance Matrix Analysis (IPMA)

*How about in Online Community Involvement?
H4b
: No significant evidence found (
-0.018
)
Major areas that management should address to improve CCO.
H1a
H1b
H2a
H2b
H3a
H3b
H4a
H4b
H5
What do they all have in common?
ANSWER = ANXIETY
Control variables:
Age and Gender
Full transcript