Denise Potosky

The Internet knowledge (iKnow) measure

Despite increasing development and administration of Internet surveys, tests, and many other applications to be used by employees and the general public, little is known about the knowledge individuals bring to Internet tasks. This research improves our understanding of the concept of Internet knowledge, and provides initial support for the construct validity of a new measure of Internet knowledge with respect to its factor structure, internal consistency reliability, and concurrent validity. From a practical perspective, clearer definition of Internet knowledge and the availability of a reliable measure of such knowledge can advance our understanding of how individuals develop Internet experience through its use and may also inform the process by which web sites and Internet applications are designed.

A Model for Predicting Computer Experience from Attitudes Toward Computers

This study examined the relationship between locus of control, two sets of beliefs about computers as electronic performance monitors, general computer attitudes, and computer experience. Results support a model in which computer attitudes mediate the relationship between an individuals locus of control and computer experience and between monitoring beliefs about computers and computer experience.

A conceptual framework for predicting the career success of IS professionals

1. ABSTRACT Given the rapid rate of change in computer technology, success in the IS profession requires that Is professionals participate in development opportunities, master new skills, learn quickly, and continually expand their skill portfolios. A conceptual framework that outlines key individual characteristics as well as important situational factors that may predict these outcomes is presented. 1.1

Some Comments on Pareto Thinking, Test Validity, and Adverse Impact: When and is Optimal and or is a Trade-Off

De Corte, Lievens, and Sackett add to the literature on selection test validity and adverse impact (AI). Their Pareto-based weighting scheme essentially asks organizations if they are willing to give up some validity to hopefully achieve some reduction in AI. We considered their approach and conclusions in relation to the regression weighting method we used, and we offer five points that reflect our observations as well as our shared goals. We hope our comments, like their work in this field, will invigorate the pursuit of new ways of examining, and one day resolving, the persistent concern regarding the AI associated with valid selection tests.

Strategic Human Resource Staffing and Organization Research: Are they One-Size-Fits-All Endeavors?

Purpose – We show that, although most private employer establishments are small, much reported research (and subsequent suggestions for practice) in management comes from large firms. In turn, we wanted to explore if organizational knowledge gained from studying one or more large firms is necessarily applicable to numerous smaller firms. Design/methodology/approach – We computed firm size in the United States using existing databases, and we then considered published literature in human resources and strategy to see if the large sample results logically applied to smaller firms. Findings – At the job-analytic level, it is suggested that jobs might be defined differently and more broadly in smaller establishments than in large organizations. Also, the feasibility of best corporate strategies may be moderated by the size of the firm. In addition, we noted that the underlying model of selection utility in human resource management (HRM), and several factors in its numerical estimation, might need to be modified as a function of firm size. Originality/value – We hope that this chapter inspires HRM and strategy researchers by helping to focus future evidence-based efforts, creating new initiatives, and providing results that are useful (or scalable) to the large number of small, private-sector U.S. firms.