The purpose of study 2 was to test how regulatory mode would affect sharing
be-havior of online video. And, the mediating role of self-disclosure between regulatory
mode and sharing behavior of online video.
3.2.1 Participants and design
60 participants were included in this experiment. There were 19 males and 41 females,
11
and the average age of participants was 24.6. All participants were randomly assigned
into two groups (assessment and locomotion). We used a short video, like in study 1. And,
we measured which way they wanted to share the video, the assessment-orientation, and
self-disclosure.
3.2.2 Materials and procedure
First, participants in different groups were presented with different regulatory mode
manipulation procedures. The regulatory modes manipulation was adopted from Avnet
and Higgins (2003). The detail procedural was showed in Appendix 1. Participants in
locomotion group were asked to recall three different experiences and describe what those
were, including “Think back to the times when you acted like a ‘‘doer’’”, “Think back to
the times when you finished one project and did not wait long before you started a new
one”, and “Think back to the times when you decided to do something and you could not
wait to get started”. Similar procedure was conducted in assessment group, but the
expe-riences which were asked to recall were different, including “Think back to the times
when you compared yourself with other people”, “Think back to the times when you
thought about your positive and negative characteristics”, and “Think back to the times
when you critiqued work done by others or yourself”. After finishing manipulation,
par-ticipants were introduced what were attached share and direct share, which was the same
as in study 1. Then they needed to answer which form they want to share this video, direct
12
share or attached share. After that, they answered the assessment measurement. Then,
they answered the self-disclosure measurement.
To measure which way participants shared, we used one question, that was “After
watched the video, you want to share it to others. Which way do you want to share it?”.
There were two options to choose, “Direct share without adding opinion, point of view,
or any description.” And “Attached share with some description, point of view, or
com-ment.”. We coded direct share 0 and attached share 1.
To measure participants’ assessment-orientation, we used the measurement adopted
from Kruglanski et al. (2000), which included 12 items. Ratings were made on a 6-point
scale ranging from 1 (strongly disagreed) to 6 (strongly agreed). The items were showed
in Appendix 2 (α=0.78). The composite score was computed by averaging responses to
each item.
To measure participants’ self-disclosure, we used the measurement adopted from
Wang & Stefanone (2013), which include 4 items. Ratings were made on a 7-point scale
ranging from 1 (strongly disagreed) to 7 (strongly agreed). The items were showed in
Appendix 3 (α=0.71). The composite score was computed by averaging responses to
each item.
3.2.3 Result
First, we run a correlation test for share method and regulatory mode, descriptive
13
statistics and bivariate correlations were given in Table 4 and Table 5. Then, we run an
ANOVA test to check manipulation. As expected, participants in assessment group tend
to be more assessment-oriented than in the locomotion group, results were showed in
Table 6. (Massessment=4.45, SD=0.63, Mlocomotion=4.09, SD=0.63, F=5.002 and p=.029).
Table 4
Descriptive statistics for study 2
Mean SD
Share method 0.7 0.462
Regulatory mode 4.27 0.650
Self-disclosure 3.53 1.287
Table 5
Bivariate correlations for study 2
1. 2 3
1 Share method 0.282* 0.376**
2 Regulatory mode 0.282* 0.343**
3 Self-disclosure 0.376** 0.343**
*p < .05. **p < .01.
14
Table 6
ANOVA test results of manipulation check for study 2
SS df MS F p
Between group 1.980 1 1.980 5.002 .029
Within group 22.960 58 0.396
Total 24.941 59
Then we run a logistic regression to predict share behavior. As expected, the
regula-tory mode was positive related with share behavior, results were showed in Table 7
(β=1.035, p=.036). Combined with result 1, we used two ways to test the relationship
between regulatory mode and share behavior of online video.
Table 7
Logistic regression results of share method on regulatory mode for study 2
β SE p Exp(β)
Regulatory mode 1.035* 0.494 .036 2.816
*p < .05. **p < .01.
To test the mediating role of self-disclosure between regulatory mode and sharing
behavior, a mediation analysis was conducted based on Baron and Kenny (1986). The
relationship between regulatory mode and share behavior have been tested (β=1.035,
p=.036). We used linear regression to test the relationship between regulatory mode and
self-disclosure. The regression analysis revealed that regulatory mode had significant
ef-fect on self-disclosure, results were showed in Table 8 (β=0.679, p=0.007). Finally, when
15
the sharing behavior was regressed on regulatory mode and self-disclosure, results were
showed in Table 8. The coefficient of regulatory mode decreased from 1.035 (p=.036) to
0.789 (p=.144). The coefficient of self-disclosure remains significant (β=0.728, p=0.017).
The result revealed that self-disclosure mediated the relationship between regulatory
mode and sharing behavior.
Table 8
Mediation of Self-disclosure between regulatory mode and share method in study 2
β p
Regulatory mode→Self-disclosure 0.679** .007
Regulatory mode→Share method 1.035* .036
Regulatory mode→Share method
Self-disclosure→Share method
0.789
0.728*
.144
.017
*p < .05. **p < .01.
16
4 General discussion 4.1 Conclusion
This research examined the moderating affect of regulatory mode toward sharing
behavior. The results of study 1 and study 2 supported that assessment-oriented people
tend to perform attached share, and locomotion-oriented people tend to perform direct
share. And, the result of study 2 demonstrated the mediating role of self-disclosure
be-tween regulatory mode and sharing behavior.
4.2 Theoretical contribution
According to the findings, this research extended the linkage between social
influ-ence and sharing behavior. The findings showed that other people’s point of view and
people’s identities in the community would influence people’s choices of sharing
behav-ior. And, it determined that different regulatory modes could influence people’s decision
of choosing the method of share and the amounts of expression.
This study also delivers a more detail understanding of sharing behavior of online
video. Previous studies focused on why people interact and share on social media, but did
not explore the detail of different sharing behavior. To address this gap, this study
dis-cusses the two different sharing, direct share and attached share, and indicate what
determine people’s choice between them.
Finally, lots of recent researches of self-disclosure focused on privacy issue, but this
17
research extended the self-disclosure literatures to sharing online video, which is
unex-plored and important nowadays. Combined with social influence theory, this research
gives a news aspect to understand regulatory mode, and connect it to self-disclosure, a
trait untested.
4.3 Practical contribution
By understanding the people’s tendency of two kinds of share, companies and
crea-tors could make different kinds of strategies on promotion, and use different stimulus to
trigger sharing for different purposes. By increasing tendency of attached share,
market-ers could get more user feedback, which is generally important for new brand marketing.
By increasing tendency of direct share, marketers could let viewers perceive the contents
they produced and the message they want viewers to focus without additional interferes.
And also, marketers could better predict viewers’ share reaction. By using different styles
or tones in the post of social media, marketers could guide the audiences to different
reg-ulatory modes and influence the method of video sharing. A guide of recalling product
using experience and comparison could lead audiences to an assessment-oriented
think-ing and make them share the experience of product or a story on their own.
Platforms, like YouTube, could improve video recommendations and auto-play list
by combining different stimulus videos or ordering adjustment to trigger a series of
viewer’s sharing behavior. For entertaining contents, it could use a bunch of dynamic
18
videos to spread the videos faster with direct share. And, for instructive videos and
un-boxing videos, it is helpful to series of informative videos to gain more perspective and
experience form viewers with attached share. That could get more discussion and extend
the life cycle of videos, and benefit this kind of knowledge creators.
4.4 Limitation and future research
There are limitations in this research. First, we collected 40 samples for study 1, and
60 for study 2. but with a larger sample, a more robust results could be revealed. Second,
this research uses one short online video form one YouTuber. Future research could
in-clude more kinds of video to extend the generality. Nowadays, the content creator, like
youtuber, tend to make their videos longer and assert more ads to gain profit. In this
re-search, we did not test the effect of those ads and video length. The further research could
include these factors to test the result. In this research, we just had participants choosing
direct share and attached share, we did not include no sharing option in studies. The future
research could extend current study to test the affect of regulatory mode on sharing or not
sharing. Taiwanese people tend to behave collectivism, compare to western countries,
people behave more humbly and are shy to express themselves. The result indicates an
important role of self-disclosure, which could differ in individualism countries. Future
research could investigate the culture difference of social influence to get more results.
19
Reference
Avnet, T., & Higgins, E. T. (2003). Locomotion, assessment, and regulatory fit: Value transfer from “how” to “what”. Journal of Experimental Social Psychology, 39(5), 525-530.
Avnet, T., & Higgins, E. T. (2006). How regulatory fit affects value in consumer choices and opinions. Journal of Marketing research, 43(1), 1-10.
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considera-tions. Journal of personality and social psychology, 51(6), 1173.
Calabrese, J. (2018, May 17). Re: State of the YouTube address — an overview of YouTube usage and growth [Web blog message]. Retrieved from
https://blog.pex.com/state-of-the-youtube-address-an-over-view-of-youtube-usage-and-growth-8d562d4b7fe
Chen, C. Y., Rossignac-Milon, M., & Higgins, E. T. (2018). Feeling distressed from making decisions: Assessors’ need to be right. Journal of personality and social psychology, 115(4), 743.
Cheung, C. M., & Lee, M. K. (2010). A theoretical model of intentional social action in online social networks. Decision support systems, 49(1), 24-30.
Cheung, C., Lee, Z. W., & Chan, T. K. (2015). Self-disclosure in social networking sites: the role of perceived cost, perceived benefits and social influence. Internet Research, 25(2), 279-299.
Cheung, C., Lee, Z. W., & Chan, T. K. (2015). Self-disclosure in social networking sites: the role of perceived cost, perceived benefits and social influence. Internet Research, 25(2), 279-299.
Cozby, P. C. (1973). Self-disclosure: a literature review. Psychological bulletin, 79(2), 73.
Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social in-fluences upon individual judgment. The journal of abnormal and social
psychology, 51(3), 629.
Ellis, D. G., & Fisher, B. A. Small group decision making: Communication and the group process. 1994. New York: McGraw-HillGoogle Scholar.
Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & management, 41(7), 853-868.
Khan, M. L. (2017). Social media engagement: What motivates user participation and consumption on YouTube?. Computers in Human Behavior, 66, 236-247.
20
Kruglanski, A. W., Pierro, A., Mannetti, L., & Higgins, T. E. (2013). The distinct psy-chologies of “looking” and “leaping”: Assessment and locomotion as the springs of action. Social and Personality Psychology Compass, 7(2), 79-92.
Kruglanski, A. W., Thompson, E. P., Higgins, E. T., Atash, M., Pierro, A., Shah, J. Y., &
Spiegel, S. (2000). To" do the right thing" or to" just do it": locomotion and assess-ment as distinct self-regulatory imperatives. Journal of personality and social psychology, 79(5), 793.
Lee, D., Yejean Park, J., Kim, J., Kim, J., & Moon, J. (2011). Understanding music shar-ing behaviour on social network services. Online Information Review, 35(5), 716-733.
Malik, A., Dhir, A., & Nieminen, M. (2016). Uses and gratifications of digital photo sharing on Facebook. Telematics and Informatics, 33(1), 129-138.
Palka, W., Pousttchi, K., & Wiedemann, D. G. (2009). Mobile word-of-mouth-A grounded theory of mobile viral marketing. Journal of Information Technology, 24(2), 172-185.
Pierro, A., Giacomantonio, M., Pica, G., Mannetti, L., Kruglanski, A. W., & Higgins, E.
T. (2013). When comparative ads are more effective: Fit with audience’s regulatory mode. Journal of Economic Psychology, 38, 90-103.
Pierro, A., Kruglanski, A. W., & Higgins, E. T. (2006). Regulatory mode and the joys of doing: effects of ‘locomotion’and ‘assessment’on intrinsic and extrinsic task‐moti-vation. European Journal of Personality: Published for the European Association of Personality Psychology, 20(5), 355-375.
Wang, S. S., & Stefanone, M. A. (2013). Showing off? Human mobility and the inter-play of traits, self-disclosure, and Facebook check-ins. Social Science Computer Review, 31(4), 437-457.
Yang, H. C., & Wang, Y. (2015). Social sharing of online videos: Examining American consumers’ video sharing attitudes, intent, and behavior. Psychology & Market-ing, 32(9), 907-919.
Zhang, S., Jiang, H., & Carroll, J. M. (2012). Social identity in Facebook community life. In Technical, social, and legal issues in virtual communities: Emerging envi-ronments (pp. 101-114). IGI Global.
21
Appendix 1
The instructions for the task, labeled ‘‘Behavior over time’’, began in the same way for all participants:
This study is about how people recall their behavior over time.
You are requested to recall three different behaviors you have used successfully in the past and to write a short example of each behavior. These are the kind of behaviors that you find people doing in everyday life.
In the locomotion condition, participants were then asked to give a short example of the following three locomotion
behaviors taken from the regulatory mode questionnaire (Kruglanski et al., 2000):
Think back to the times when you acted like a ‘‘doer’’.
Think back to the times when you finished one project and did not wait long before you started a new one.
Think back to the times when you decided to do something and you could not wait to get started.
For the assessment condition, they were asked to give a short example of the following three assessment behaviors taken from the same questionnaire:
Think back to the times when you compared yourself with other people.
Think back to the times when you thought about your positive and negative characteris-tics.
Think back to the times when you critiqued work done by others or yourself.
22
Appendix 2
Assessment items (6-point scale where 1 = strongly disagree and 6 = strongly agree)
1. I never evaluate my social interactions with others after they occur. (reverse-scored)
2. I spend a great deal of time taking inventory of my positive and negative character-istics.
3. I like evaluating other people's plans.
4. I often compare myself with other people,
5. I don't spend much time thinking about ways others could improve themselves. (re-verse-scored)
6. I often critique work done by myself or others.
7. I often feel that I am being evaluated by others.
8. I am a critical person.
9. I am very self-critical and self-conscious about what I am saying.
10. I often think that other people's choices and decisions are wrong.
11. I rarely analyze the conversations I have had with others after they occur. (reverse-scored)
12. When I meet a new person I usually evaluate how well he or she is doing on vari-ous dimensions (e.g., looks, achievements, social status, clothes).
23
Appendix 3
1. I often talk about my feelings on social media.
2. I often post something about my relationships and private life on social media.
3. I often post photos of me and my friends on social media.
4. I often express my thoughts and true self completely on social media.