Paul Kauffmann

Are Math Readiness and Personality Predictive of First-Year Retention in Engineering?

ABSTRACT On the basis of J. G. Borkowski, L. K. Chan, and N. Muthukrishnas model of academic success (2000), the present authors hypothesized that freshman retention in an engineering program would be related to not only basic aptitude but also affective factors. Participants were 129 college freshmen with engineering as their stated major. Aptitude was measured by SAT verbal and math scores, high school grade-point average (GPA), and an assessment of calculus readiness. Affective factors were assessed by the NEO–Five Factor Inventory (FFI; P. I. Costa & R. R. McCrae, 2007), and the Nowicki–Duke Locus of Control (LOC) scale (S. Nowicki & M. Duke, 1974). A binary logistic regression analysis found that calculus readiness and high school GPA were predictive of retention. Scores on the Neuroticism and Openness subscales from the NEO-FFI and LOC were correlated with retention status, but Openness was the only affective factor with a significant unique effect in the binary logistic regression. Results of the study lend modest support to Borkowskis model.

A New Market Adoption Model for the Information Systems Industry

Abstract: The information systems (IS) industry has challenges in the effectiveness of product development because new product failures are a significant problem. High failure rates of IS projects suggest that organizations need to improve their ability to forecast market adoption of their products. This study first reviews several aggregate diffusion models based on selection criteria created according to the needs of the IS industry. It then concludes that developing a new market penetration model based on the criteria is helpful to the IS product development process. The new model is formulated by using conjoint analysis and a purchase decision simulator. The functionality of the model is also demonstrated on the sales data global positioning systems (GPS). Forecasting the life cycles of technical products such as IS is essential for engineering managers to develop products with potential market success. As a result, this research contributes to the engineering management body of knowledge by providing two beneficial outcomes: (1) a brief survey of market adoption models to engineering managers, and (2) a new model for engineering managers, particularly for the ones working with IS, to support their new product development decisions based on forecasts on future market adoption of their products.

Criteria for Fleet Management: Identification of Optimal Disposal Points with the Use of Equivalent Uniform Annual Cost

This paper presents a decision model developed to identify the optimal asset life for six equipment classes, including three on road and three off road. This model was developed as an element of a comprehensive study to identify a methodology to evaluate aging (or depreciation), disposal points, and overall utilization. The asset life optimization model discussed in this paper is a core result of that study and presents the opportunity to reduce overall cost, improve the age of the fleet and its readiness to serve the public, and improve overall utilization. This paper examines salvage values and identifies trend models for market value decline on the basis of historical records. With the use of internal cost information, the model identified trends in cost of operation and use as equipment aged. This information was integrated into an optimal economic life model on the basis of equivalent uniform annual cost to identify the optimal disposal point for the six classes. The analytical models developed in the study provide a foundation for long-term analysis of fleet size and the cost-effectiveness of disposal points.

Are Distance Laboratories Effective Tools for Technology Education

The ability to perform a laboratory experiment as a nonhands-on observer, such as in a distance education context, has been questioned by some educators who ponder whether distance education lab courses are as effective as those held in a physical laboratory environment. This article examines this issue and compares the performance of distance education students with their on-campus counterparts in a junior laboratory course. Data from six semesters are examined and presented. A regression model is developed to predict the performance of both distance education and on-campus students. Results of the model show that only report grades and location (whether distance education or on-campus) are statistically significant. In addition, statistical analysis of the six semesters of data shows equal performance of the two groups.

Integration of Quality Cost into a Total Cost Model for a Distribution Network

Abstract Effective supply chain management requires integration of the interconnected operational steps from raw material supplier through production, distribution, and final product delivery. These links must operate effectively and efficiently for the supply chain to achieve its primary objective: increased customer value at each step. Distribution systems are particularly critical components in supply chain networks since they are often the last direct interface with the customer. As a result, distribution error in the supply chain cannot be corrected and will impact customer satisfaction, ultimately leading to possible lost sales or customers.