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  • 1. Lee, Chan Perceived job change toward dimensions of knowledge work among three levels of employees in a Korean bank

    Doctor of Philosophy, The Ohio State University, 2004, Educational Studies: Hums, Science, Tech and Voc

    The purpose of this study was to explore the perceived job change toward dimensions of knowledge work among frontline employees, middle managers, and senior managers in a large Korean bank. This study examined their perceived job change in terms of frequency, importance, and difficulty. The instrument used in this study was from the questionnaire of the Occupational Information Network (O*NET), which is an updated version of the Dictionary of Occupational Titles (DOT) that has been employed for job analysis since the 1930s. From the 18,000 employees of the target population, 377 employees were randomly selected. Using an Internet survey, a total 359 of employees responded. Thus, the response rate of this study is 95 percent. The results of study showed that all four of the dimensions of knowledge work increased in terms of importance, frequency, and difficulty. Results from a series of paired t-tests indicated that all three job levels rated the four dimensions of knowledge work higher today than as performed three years ago. The results suggested that increasing aspects of knowledge work have been a prominent part of all three job levels. However, results from one-way ANOVA showed the degree to which each of the job levels experienced change toward knowledge work differed. In particular, frontline employees and middle managers have been subject to relatively more change toward knowledge work than senior managers. Findings supported that knowledge work is no longer the monopoly of senior managers. The conclusions of the study can be summarized as follows: (1)There were changes toward knowledge work across all three job levels.(2) Change toward knowledge work seemed to have differentially affected some job levels more than others.(3) Change toward knowledge work seemed to have affected frontline employees and middle managers more than senior managers.

    Committee: Jacobs Ronald (Advisor) Subjects:
  • 2. KHALIL, AHMED WORK COMPATIBILITY: AN INTEGRATED DIAGNOSTIC TOOL FOR EVALUATING HUMAN PERFORMANCE IN EMERGING ENTERPRISES

    PhD, University of Cincinnati, 2003, Engineering : Industrial Engineering

    Background. Advances in human-based systems have progressed at slower pace than those for technological systems in emerging enterprises. This is largely attributed to the complex web of variables that jointly influence work outcomes, hence, resulting in a lack of comprehensive quantitative methodology to solve this complexity. Objective. The study objective is to develop and validate work compatibility as a diagnostic tool to evaluate human performance in emerging enterprises. Work compatibility is defined as a latent variable integrating the positive and negative impact characteristics of work-related variables in the human-at-work system in the form of a prescribed relationship. Development Tasks. The theoretical basis of work compatibility is described at length in terms of concepts and model. In addition, approximate reasoning solutions for the compatibility variables are presented in terms of three models, namely, linear, ratio, and expert. Validation Tasks. The work compatibility construct has been tested on fifty-five service workers in a hospital setting, with reference to severe musculoskeletal and high stress outcomes. The results have demonstrated that the expert compatibility model provided the stronger and more significant associations with work outcomes in comparison to the linear and ratio compatibility models. Conclusions. Although the work compatibility validation is limited by both the cross-sectional design and sample size, the findings of this explanatory investigation suggests that it is worthwhile to further investigate the work compatibility construct as a diagnostic tool to evaluate human performance issues in emerging enterprises.

    Committee: Dr. Richard Shell (Advisor) Subjects: Engineering, Industrial