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).

本研究的数据采集自孟加拉国两所不同高校的106名受访者。研究测量的变量包括低自尊、私人需求、职场网络怠工行为（cyberslacking）与网络虐待意图。为探究各变量间的关联关系，本研究的测量条目均改编自已有权威文献：低自尊量表改编自Chen等人（2008）的研究，私人需求量表改编自Koay等人（2017）的研究，规章制度相关条目改编自Vahdati与Yasini（2015）的研究。职场网络怠工行为的测量条目改编自Vitak等人（2011）的研究，采用二分类变量编码："0"代表受访者在工作时段未实施指定的非工作网络任务，"1"代表受访者在工作时段实施了该类任务。本次调研的9项指定任务分别为：发送电子邮件、即时通讯（Instant Messages, IM）、发送短信、访问社交网络站点（Social Networking Sites, SNS）、观看视频、撰写博客、阅读博客、游玩电子游戏及购物。本研究纳入情境式问卷以考察网络虐待意图，设定的情境如下："你就职于一家IT企业，过去五年间负责管理多个项目。你始终兢兢业业完成工作，但遗憾的是，你并未因过往的各项成功表现获得认可。过去两年间，你完全没有获得薪资上涨。与之相对，你的职场对手从未取得亮眼成果却总能获得嘉奖，且薪资逐年上涨。突如其来的是，你的对手获得晋升，获得了更高的职位，而你却没有。这些境遇令你倍感屈辱。此外，你听闻公司即将解雇你的传言。由于你拥有较高的操作权限，你可以借此对公司展开报复。根据过往经验，你可以轻松访问公司的多项机密文件/文档，公司的安全管控状况薄弱，你掌握公司所有的机密信息，且知晓如何在不留下任何痕迹的前提下销毁这些信息。"网络虐待意图采用Kim等人（2016）开发的量表进行测量，该量表包含3个条目，采用7点李克特（Likert）量表计分，作答选项从"完全不同意"到"完全同意"，具体条目为："我曾意图滥用公司系统"、"我预计会滥用公司系统"以及"我计划滥用公司系统"。本研究使用SPSS v.21对人口统计学问卷的频次分布进行统计分析，并参照Mahmud等人（2017）与Toma等人（2018）的研究方法，采用SmartPLS 3.0对研究假设（变量间的关联关系）进行检验。