ABSTRACT. The ‘digital mindset’ is frequently raised by both researchers and practitioners to be an essential factor of the human side of digitalization to successfully cope with the arising chal-lenges of digitalization. Despite existing conceptualizations of the construct, the literature provides no operationalization for quantitative research, so far. Our research pursues the goal to address the question of how the digital mindset can be measured. Literature- and Delphi study-based approaches were used to develop various types of scales which were pre-validated by experts and statistically validated. For conten-tual validation, 26 participants were interviewed and subse-quently completed the developed scales in a panel study. The resulting interview statements were rated by two independ-ent raters and the results compared with the scale results. The correlations of the answers from using the different measures indicate that the developed survey scales can serve as prox-ies for the qualitative approach, which is assumed to measure the ‘true’ level of the digital mindset. In the future, research-ers can choose from different scales based on their require-ments for precision and efficiency (i.e., time needed to com-plete the survey items).

ABSTRACT. E-learning is one of the recent trends and major technological advancements in Information Technology. It has gained even more popularity during the last year since a global pandemic caused by corona virus disease has brought countries all over the world to a standstill. Social distancing was adopted to reduce the spread of the virus, while governments worldwide responded to the emergency situation with educational institutions closures, shifting traditional teaching in classrooms to online learning. Information Systems (IS) such as e-learning implementation in higher education is a large investment. Such investments are expected to bring increased efficiency and effectiveness, as well as better quality services to stakeholders even if the COVID-19 impact is getting institutions to stand still. The purpose of this research is then to investigate success factors of e-learning systems that paves way towards theory development that will result in better online educational quality in spite of the pandemic challenge.

ABSTRACT. Natural catastrophes, human-made disasters, or as most recently pandemics can force governments to impose telework for their citizen. With Twitter data from the Covid-19 time, where telework was required in Great Britain for certain periods, we look at employees’ experience of telework. Our preliminary results indicate a more positive perception of telework while it was enforced due to Covid-19 restrictions, compared to a regular telework period. In our future research, we plan to deepen the understanding of the employees’ topics of concern and to develop a model explaining how enforcement affects their perception of telework.

ABSTRACT. This study conducts a historical review of two decades of SIGMIS conferences (2000 to 2019), using scientometric methods to identify the most frequent authors as well as the most frequently-cited papers and panels. We identify the leading contributing authors during the 20-year period, as well as during the two decades. We also list the most-cited papers and introduce the title, topic and research methods of a dozen leading papers. Based on the larger number of conference items with moderately-large citations and above (using the threshold of 3.0 or more citations per year since publication) during the earlier decade (2000-2009) than in the recent decade (2010-2019), we consider various explanations for why this may be so. Finally, we compare citations to downloads to argue that they are separate measures of research impact that are not always highly correlated.

ABSTRACT. Security awareness professionals are tasked with implementing security awareness programs within their organizations to assist employees in recognizing and responding to security issues. Prior industry-focused surveys and research studies identified desired skills for these professionals, finding that many are ill-prepared due to gaps in professional skills (e.g., communication, interpersonal) and a lack of recognition of the unique awareness role. However, it is unclear if these findings are similar for security awareness professionals in the United States (U.S.) federal government sector in which awareness plays an important part in teaching employees how to protect sensitive national and citizen data. To identify the current roles, professional backgrounds, and desired knowledge and skills for government security awareness professionals, we conducted a two-phase research study that leveraged focus group and survey methodologies. Insights gained from these results can inform guidance and other initiatives to aid organizations in building security awareness teams with the appropriate competencies. While focused on the U.S. government, findings may also have implications for other sectors and countries.

ABSTRACT. Recent events have demonstrated the danger of online conspiracy theories to cause harm in the real world. In this research in progress, we focus on machine learning techniques to differentiate conspiracy information from other forms of misinformation. Our results demonstrate that conspiracy language is differentiable and suggest there may exist features of conspiracy language independent of the conspiracy topic. We also present a direction for future work to better understand the unique features of conspiracy language and how they may be used to enhance machine learning techniques.

ABSTRACT. This paper develops the concept of accidental insecure behavior (AIB) by noting that many insecure behaviors in organizations are not intentional violations of policy but unintended accidents. These behaviors are costly to businesses and users, but most IS research has focused on intentional behaviors. We use the systems theory of accident causation to develop our model of AIB. Implications and future research directions are given.