I’ve read the paper “Using social media for work: Losing your
time or improving your work?” by Ioannis Leftheriotis and Michail N.
Giannakos. The paper was published in Computers in Human Behaviour, which has an impact factor of 2.067
(2013) and the articles are being peer-reviewed, confirming the high quality. The
main purpose of the study is to see if social media is being used in the
workplace and if it’s related to the workers performance? The study contains
1799 people from 33 different companies working in the insurance sector in
Greece and the main research questions are:
- RQ1: Do the employees of insurance industry make use of social media for work purposes?
- RQ2: What motivations (values) does someone have for using social media for work purposes?
- RQ3: Does the use of social media for work impact employees' work performance?
(Leftheriotis & Giannakos, 2013)
To answer these
questions questionnaires were handed out at the companies (83%) or performed
online. The employees had a total of 2-3 days to finish the questionnaire
before the researchers returned to pick them up (the online surveys were open
for 2 months). The attendance in the study was voluntary and no rewards were
handed out to the participants.
The benefits of using
questionnaires are the fact that they are easy to hand out, you get a lot of
information and they are easy to analyze. Meanwhile, the possibilities for
misinterpretation of the questions are higher, than say, during an interview
where the participants could ask for explanations to terms they don’t
understand (Wikipedia, 2013b). That’s why I like the fact that the term “social
media” was presented with examples such as Facebook, Twitter, Blogs and LinedIn
in order for the participants to fully understand the term. The questions about
perceived motivation was measured on a 5-degree scale from “Strongly disagree”
to “Strongly agree” which is an a widely used and accepted instrument in
research (Cohen et. al., 2000:253) that makes the analyzing of the answers
easier.
In order to be certain
that the data they received from the questionnaires are reliable the
researchers makes several types of reliability and validity checks. I don’t
have to much knowledge about this from before so it was nice to see the amount
of work it took for them just to establish the fact that the data was correct
(even though they don’t go into the exact methods being used).
The study was conducted almost equally
between men (52%) and women (48%), with a variety of age groups and with a
large number of people (1799), but there are still some limitations. The
authors present a couple at the end of the paper; the study was made only in
Greece and only within the insurance sector, which makes it questionable if you
can generalize the results further. Another limitation is the fact that the work
performance is measured from the employee’s self-assessment, which could make
it biased.
But the biggest mistake I think is the
fact that they don’t make a clearer distinction between the different social
networks. If such a distinction had been made, they would be able to
say which social networks are contributing to the performance and which are
not. Now they just bunch them all together, and maybe some social networks are
far better than others at contributing to the work performance, but sadly we
don’t know if that’s the case now, since they never ask a more specific
question of which social network(s) the participants are using.
Quantitative
methods vs. Qualitative methods
One advantage of using
questionnaires is the fact that it’s easy to hand out if you’re using online
forms. You also get a higher response rate than if you were to mail them out
physically (Fondell et. al., 2010). Another positive way of using the high
number of participants as Fondell et. al. did is that it’s easier to draw
conclusions and in some way make generalizations about the results. A
limitation, as I wrote earlier, is the possibility for misinterpretation from
the participants.
If Fondell et. al.
would have wanted to get more qualitative data they may used interviews or focus groups instead. While they don’t give as much data, they could be beneficial if you
want more specific information on particular cases. Qualitative methods explain
the how’s and why’s. They give room for interpretation (Wikipedia 2013a), which
could be both positive and negative.
Resources
Cohen,
L., Manion, L., & Morrison, K. (2000). Research methods in education.
London: Routledge.
Fondell, E., Lagerros, Y. T., Sundberg,
C. J., Lekander, M., Bälter, O., Rothman, K., & Bälter, K. (2010). Physical activity, stress, and self-reported upper
respiratory tract infection. Med Sci Sports Exerc, 43(2), 272-279.
Leftheriotis, I., & Giannakos, M. N. (2013).
Using social media for work: Losing your time or improving your work? Computers
in Human Behavior, 31(0), 134–142.
doi:http://dx.doi.org/10.1016/j.chb.2013.10.016
Wikipedia (2013a). Qualitative research. http://en.wikipedia.org/wiki/Qualitative_research (2013-11-29)
Wikipedia (2013b). Questionnaire. http://en.wikipedia.org/wiki/Questionnaire (2013-11-29)
Interesting that they did several tests for reliability and validity. I think that can be a big issue when working with quantitative methods and especially questionnaires. People may not answer truthfully or they just misinterpret the questions. As you say, they did good in the questionnaire because they gave examples about different social medias in order for people to understand the question fully. I feel that mostly this help text is nowhere to be found when you get to do these surveys and many times it can definitely be needed. I am wondering more about those checks for reliability and validity, did they say anything about how these were done?
SvaraRaderaYes, they did... And I will try to summarize it the best that I can, if that isn't enough I suggest that you read the article (the part about reliability and validity is just a short part).
RaderaFirst they wanted to be sure that the scale they used were correct and reliable, in order to assess that they used something called an analysis of composite reliability. They quickly mentions that the Cronbach's alpha variable (http://en.wikipedia.org/wiki/Cronbach's_alpha) is acceptable and then moves on.The number should be somewhere between 0-1, the higher the better and they got values of about 0.83-0.95.
Then they continued to evaluate the reliability of the measure. Which they did by "measuring its factor loading onto the underlying construct". I'm not quite sure what this means...
To determine a good convergent validity they assessed the Average Variance Extracted (AVE) which "measures the overall amount of variance that is attributed to the construct in relation to the amount of variance attributable to measurement error". So, I guess that means that the AVE is a measure of the error-free variance of a set of items i.e. questions? Apparently the number should be over 0.5 and with values ranging from 0.54-0.73 they clearly met those goal.