Download - Why people stop using sina weibo?
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Why People Stop UsingSina Weibo?
Final Year Project 2014
Aoran YangHayden Chen
+Welcome!Aoran YangHayden Chen
+AcknowledgementsTo:Dr. May WangDr. Daniel Cheung
+MotivationWhy People Stop Using Sina Weibo?
+Sina Weibo
The biggest Chinese micro-blog Website.
A leading social media platform designed for people to create, share and discovery.
5 hundred million users. (2013Q4)
+Sina Weibo has Challenge
“Our challenge:Our ability to execute the strategy faces a number
of risks and uncertainties, including the following:
- Maintain and increase our active user base, as well as the ability to maintain and increase the degree of user involvement;
”
+Report from China Internet Network Information Center (CNNIC)
China's Weibo users decline 27.83 million, a decrease of 9.0%.
Weibo’s usage decreased by 9.2%. (December 2013)
+King-wa Fu’s Research at HKU
There are several millions of users create about 94% of the content on Weibo, about 200 million users just repost these contents.
A survey found that 58.8 percent of the account prior to January 3, 2014 did not post any Weibo. Only 5% Weibo users are active users.
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Why people stop using Weibo?Our Questions
+Literature reviewsWhy people stop using Sina Weibo?
+Fundamental ModelsLiterature Reviews
+Technology Acceptance Model (TAM) the most widely accepted model of user acceptance
and usage. TAM helps better understand the influence of several
factors on the key dependent variable —Intention.
+Theory of planned behavior (TPB)
TPB is adopted in improving understanding of the determinants of information technology usage.
The extended TPB has been successfully used in predicting IT usage from decomposing attitudinal, normative and control beliefs.
Many researches have adopted the key dependent variable of —Frequency (Beale & Manstead, 1991; Schlegel, DAvernas, Zanna, DeCourville, & Manske, 1992)
+Social PresenceLiterature Reviews
+Social Presence
The degree of social presence in the medium determines how sociable of a medium.
High perceived social presence would have a greater impact on influencing individuals, to join and to continue using an online social networking website. (Flanagin and Metzger, 2001)
Individuals tend to select the medium that they perceive to have the highest social presence.
+Content QualityLiterature Reviews
+Content Quality
Content quality refers to the inherent value and usefulness of the information provided by web services. (Huizingh, 2000)
There are 4 intrinsic data quality specify whether data is complete, unambiguous, meaningful, and correct. (Wand and Wang, 1996)
Chae et al. (2002) proposed that the objective and credible information that is highly relevant to the users’ task should be provided on users interfaces simultaneously, and shall adopt items from “Intrinsic quality” and “Contextual quality” of Information Quality (IQ)
+Perceived Ease of Use Literature Reviews
+Perceived Ease of Use
Perceived ease of use refers to “the degree to which a person believes that using a particular system would be free of effort.” (Davis, 1989)
Perceived ease of use create a favorable disposition or intention toward using the IT that consequently affects its intention and frequency in usage.
+TrustLiterature Reviews
+Trust
Trust is the belief that the exchange party is able to fulfill its obligation reliably and confidently. (McKnight & Chervany, 2001)
Trust is motivated to seek mutually beneficial gains (Morgan & Hunt, 1994), and will refrain from abusing the relationship (Voss, Sirdeshmukh, & Voss, 2008).
Previous studies (K.-Y. Lin & Lu, 2011) have indicated that trust motivates users’ intention to use SNSs. Consequently, H.-F. Lin (2006) also included trust as one of the factors in analyzing behavioral intention to participate in virtual communities.
+DistrustLiterature Reviews
+Distrust
Cho (2006) investigated the way consumers’ evaluations of an e-business operations relate to their judgments of distrust, and how such judgments shape consumer distrust.
Distrust proposed as a “expectation of injurious action,” Specifically, distrust is a belief that a partner will be incompetent (Lewicki, McAllister, & Bies, 1998), exhibit irresponsible behavior, and will not care about one’s welfare or even intend to act harmfully (Sitkin & Roth, 1993).
+EnjoymentLiterature Reviews
+Enjoyment
Enjoyment is an intrinsic motivation in adopting technology.
Davis, Bagozzi, and Warshaw (1992) referred enjoyment as the extent to which the activity of using a computer system is perceived to be personally enjoyable.
Prior research proposed enjoyment as a determinant of behavioral intention (Davis et al., 1992; Venkatesh et al., 2002). Besides, Dholakia, Bagozzi, and Pearo (2004) included entertainment value in the study of consumer participation in virtual communities.
+Subjective NormLiterature Reviews
+Subjective Norm
Subjective norm determines the changes in attitudes and actions produced by social influence.
Subjective norm reflects the influence and compliance of expectations from significant others (Kelman, 1958). In previous research, the compliance process appeared to be paramount (Cheung et al., 2011).
According to Cheung et al. (2011), before users have any actual usage experience with a new system, the second-hand information, especially from the primary reference groups (family or friends), are important for their usage decisions and intentions.
+MethodologyWhy People Stop Using Sina Weibo?
+Research Model
+The Survey
The questionnaires are developed from material discussed and tested previously;
The items were slightly modified to suit the context of Sina Weibo.
Each item was measured on a five-point scale, ranging from ‘‘disagree strongly’’ (1) to ‘‘agree strongly’’ (5).
+Data Analysis
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+Data Collection
Data Analysis
RESPONDENTS RELIABILITYTEST
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N=254
Invalid Questionnaires
N=215
RELIABILITY TEST
Latent Variables Cronbach's Alpha N of Items
Content Richness
.923 2
Content Accuracy
.738 3
Content Timeliness
.545 3
Ease of use
.157 4
Enjoyment
.920 3
Latent Variables Cronbach's Alpha N of Items
Trust
.896 12
Distrust
.866 10
Subjective Norm
.862 2
Social Presence
.899 3
Intention
.764 2
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+Structured Equation Model (SEM)Data Analysis
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Empirical Analysis
GFI/AGFI .682/.583Pass the general
examination
RMR, GFI
Model RMR GFI AGFI PGFI
Default model .130 .628 .582 .559
Saturated model .000 1.000
Independence model .198 .215 .178 .206
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Empirical Analysis37
+ResultData Analysis
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Hypothesis
(Social Presence)
Test Result
(Supported√ /Not
Supported× )
Hypothesis
(Intention)
Test Result
(√ /× )
Hypothesis
(Frequency)
Test Result
(√ /× )
H1 Trust √ H3 Content Richness
√ H12 Content Richness
√
H2 Enjoyment √ H4 Content
Accuracy × H13
Content Accuracy
√
H5 Content
Timeliness × H14
Content Timeliness
×
H6 Ease of
Use × H15
Ease of Use
√
H7 Trust × H16 Trust √
H8 Distrust × H17 Distrust √
H9 Enjoyment √ H18 Enjoyment √
H10 Subjective
Norm × H19
Subjective Norm
√
H11 Social
Presence √ H20
Social Presence
×
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+LimitationsData Analysis
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---May lead to Misinterpretation
User Number Limitations
Region Restrictions
---Bias Significance Level&Result
Certain Words Changed to Adapt our Research
RESPONDENTS QUSTIONNAIRE
Limitations
+Coclusion & Recommendations
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Hypothesis
(Social Presence)
Test Result
(Supported√ /Not
Supported× )
Hypothesis
(Intention)
Test Result
(√ /× )
Hypothesis
(Frequency)
Test Result
(√ /× )
H1 Trust √ H3 Content Richness
√ H12 Content Richness
√
H2 Enjoyment √ H4 Content
Accuracy × H13
Content Accuracy
√
H5 Content
Timeliness × H14
Content Timeliness
×
H6 Ease of
Use × H15
Ease of Use
√
H7 Trust × H16 Trust √
H8 Distrust × H17 Distrust √
H9 Enjoyment √ H18 Enjoyment √
H10 Subjective
Norm × H19
Subjective Norm
√
H11 Social
Presence √ H20
Social Presence
×
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+
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CONTENT RICHNESS
ENJOYMENT
Intention
CONTENTACCURACY
SOCIAL PRESENCE
Frequency
SUBJECTIVENORM
+
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EASE OF USE TRUST DISTRUST
Eliminate useless utilities
Simplify manipulation procedures
Clean the Internet environment,
Delete information like advertisements, Internet frauds, and fake fans
Frequency
HighMarket Share
Low
Mar
ket
Gro
wth
Value-added Information
Frequency
Prioritize
milk and invest
Intention
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Taking on Future OpportunitiesStrategy
Hig
hLo
w
?
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Differentiation:Customer
loyaltyFocus:Market
Segment
……Grand Strategy : Concentric Diversification
Innovative online communitiesClose to the core markets
2014 2015 2016 2017
Reduce in “Intention Business”
Strategy