Lucian L. Visinescu

Text-mining the voice of the people

Statistical techniques help public leaders turn text in unstructured citizen feedback into responsive e-democracy.

The influence of website dimensionality on customer experiences, perceptions and behavioral intentions: An exploration of 2D vs. 3D web design

Abstract As online retailers seek to attract customers through innovative electronic storefront designs, some are experimenting with three-dimensional (3D) websites. This study examines the influence of website dimensionality on cognitive absorption, perceived ease of use, and, indirectly, perceived website usefulness and intentions to buy online using the website. Findings indicate that shopping websites using 3D environments are associated with lower perceived ease of use and lower cognitive absorption, compared to traditional 2D websites. The effect of website dimensionality on cognitive absorption is moderated by user experience. The implications of the study for research and practice are discussed.

Orthogonal rotations in latent semantic analysis: An empirical study

Abstract The Latent Semantic Analysis (LSA) literature has recently started to address the issue of interpretability of the extracted dimensions. On the software implementation front, recent versions of SAS Text Miner ® started incorporating Varimax rotations. Considering open source software such as R, when it comes to rotation procedures the user has many more options. However, there is a little work in providing guidance for selecting an appropriate rotation procedure. In this paper we further previous research on LSA rotations by introducing two well-known orthogonal rotations, namely Quartimax and Equamax, and comparing them to Varimax. We present a study that empirically tests the influence of the chosen orthogonal rotations on the extraction and interpretation of LSA factors. Our results indicate that, in most cases, Varimax and Equamax produce factors with similar interpretation, while Quartimax tends to produce a single factor. We conclude with recommendations on how these rotation procedures should be used and suggestions for future research. We note that orthogonal rotations can be used to improve the interpretability of other SVD-based models, such as COALS.

Information technology literacy revisited: an exploratory assessment

This study examines student perceptions and usage of a variety of information technologies, their comfort level in performing basic computer related tasks, and their computer related experience and sources of learning about information technology. Findings are interpreted through a systems thinking perspective with a focus on the implications for information technology educators. Although students today have more exposure to information technology than their counterparts of a decade ago, these findings indicate that they still do not perceive the classroom as a major source of learning about it. Exploratory analysis, however, reveals that greater classroom exposure to information technology is positively related to a variety of factors.

Analysis of Protective Behavior and Security Incidents for Home Computers

ABSTRACT This study analyzes the factors that affect security protective behavior and perceived security incidents. Protective behavior is found to have a positive impact on the perceived security incidents, especially for the more educated home computer user. Human factors such as “perceived barriers” (to use new security software tools), “self-efficacy” (confidence), and “cues to action” (awareness) are found to influence both the protective behavior and perceived security incidents.

Improving Decision Quality: The Role of Business Intelligence

ABSTRACT This exploratory study provides a validated, parsimonious research model of antecedents of the perception of the quality of decisions made using business intelligence support. Findings provide insight into little investigated avenues such as the role of problem space complexity in perceived decision quality as well as indicate a more complex interplay among the antecedents of decision quality than heretofore examined. For example, results suggest that there may be a tipping point for which information quality and use of the system support higher perceived decision quality. In addition, these findings provide a direction for future research to generate deeper, more meaningful contributions in our collective understanding of how business intelligence (BI) serves to improve the quality of decision-making.

Better Safe than Sorry: A Study of Investigating Individuals’ Protection of Privacy in the Use of Storage as a Cloud Computing Service

ABSTRACT Since the use of network-based storage as a cloud computing service [Storage as a Service (StaaS)] becomes ubiquitous, users who store data in the cloud are exposed to risk and potentially severe consequences. Therefore, individuals should carefully consider security and privacy issues when using StaaS. Drawing upon the principle of self-preservation and the theory of protection motivation, this study develops a research model explaining the mechanisms leading to the development of a protection strategy for individuals’ safe use of StaaS and empirically tests the proposed model. The results show that the natural propensity to trust, an individual trait, influences an individual’s need for privacy. This, in turn, along with perception of privacy risk, significantly affects individuals’ perception of the need to protect themselves. Three coping appraisal factors, preventive measures, self-efficacy, and willingness to incur cost of prevention, together with the individual perceived need to protect self, directly and positively affect users’ need to develop a protection strategy in a cloud computing environment. Theoretical and practical implications are discussed.

Using Text Mining Analytics to Understand IT Internal Control Weaknesses

This study aims to examine the antecedents and consequences of IT Internal Control Weaknesses (ITICWs). Specifically, we propose a comprehensive model to examine the impact of IT governance on ITICWs as well as effects of ITICWs on firm performance. To gain deep insight into ITICWs, we propose to apply text mining analytics to categorize different types of ITICWs. This allows us to examine the impact of different categories of ITICWs on firm performance. We are in the process of collecting the data.