Cyberslacking and Internet Abuse Intention Data Set

Data was collected from 106 respondents from two different universities in Bangladesh. The items measured low self-esteem, private demand, cyberslacking behavior and abusive intention. To
measure the relationship with the variables, we adapted the items from
established literature. Items for low self-esteem was adopted from the research
of Chen et al. (2008), items for private demand was adopted from the work of
Koay et al. (2017), rules and regulations were adopted from the research of Vahdati and Yasini, (2015). Cyberslacking was
identified from (Vitak et al., 2011) and measured it using binary variables
where “0” means respondents did not do the questioned tasks at work and on the
other hand “1” means respondents did the questioned tasks while they at work.
The questioned nine items are “sending emails”, IM (Instant messages)”,
“Texts”, “Visiting a SNS (Social Networking Sites)”, “Watching video”, ”Writing
blogs”, “Reading blogs”, ”Playing video games” and “Shopping”.

We included a scenario based questionnaire to investigate the
internet abuse intention. The scenario was “You work for an IT farm; and for
last five years, you managed several projects. You are always dedicated to your
work but unfortunately you are not appreciated with all of your successful
aspects. Your salary increment is totally off for last two years. On the other
hand, your rival is always credited without doing successful perspectives as
well as his/her salary increment is going on day by day. All on a sudden, your
rival is promoted for higher designation but you are not. These situations are
humiliating for you. You also hear a rumor that the farm may be fired you soon.
If you want, then you may take revenge against the company because of your high
liberty. From your past experience, you know that you can access several
confidential files/documents easily. The security control situation at the
company is poor. You know all of the confidential information of your company
and also know how to destroy all of those information without leaving any
evidence”. Abuse intention was measured using the scale from (Kim et al., 2016)
consisting of three items with response options varying from strongly disagree
to strongly agree in the seven point Likert scale format. The included items
are “I intended to abuse the systems”, “I predict I will abuse the systems” and
“I plan to abuse the systems”.
We
used SPSS v.21 to calculate the frequency of demographic questionnaire.
SmartPLS 3.0 was used to test the hypotheses (relationship between the
variables) by following the research of Mahmud et al. (2017) and Toma et al.
(2018).