In a small, owner-managed, knowledge work firm, assessments were completed on the owners as a method to complete job analysis—surfacing tacit knowledge such as personal characteristics, cognitive style, values and philosophy that contributed to success. Business strategy is often strongly influenced by the tacit knowledge and competencies of the owners, and their unique perspective on the company and marketplace.

We study three models of job scheduling in a distributed server system. For each of them we suggest scheduling algorithms that are computationally efficient and provably achieve a performance objective related to the model. For this we consider jobs to be an abstraction of executable programs that request specific resources e.g. memory, CPU. Resources need to be reserved in one of the servers for the duration the programs run, which is unknown. The first model considers queue-based scheduling algorithms, in which jobs belong to a finite set of types and each type has a separate queue. The scheduling objective under this formulation is to keep the size of all queues bounded, which translates to bounded queuing delay. The two families of algorithms for this model can achieve the objective for the maximum theoretical workload. Most importantly they follow vastly different paradigms and are both viable alternatives depending on what other trade-offs the scheduling has to achieve. The second model considers that resource requirements of jobs come from an unknown distribution. Jobs are queued and the objective is again to keep the number of jobs in the queue bounded and consequently the queuing delay. In this harder formulation there is no previous characterization of the maximum workload that can achieve the objective. We provide such a characterization and algorithms that achieve at least 2/3 of that maximum. Lastly, we consider a model without queues in which jobs are admitted or rejected on arrival, with the goal to maximize the total utility of the jobs that run. Algorithms of this model were proven to achieve at least 1/2 of the maximum, but further analysis suggests that this limit can be as high as 1 − e (exponent -1). In all models we made simplifying assumptions that allow us to prove the desired properties of the system, but despite the theoretical nature of this work, we also discuss how the algorithms can be applied and tailored to the needs of different cloud applications. We hope they will eventually inspire improvements to existing cloud infrastructure management deployments.

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Despite the importance of job specifications to much of industrial and organizational psychology, little is known of their reliability or validity. Because job specifications are developed based on input from subject matter experts, interrater agreement is a necessary condition for their validity. The purpose of the present research is to examine the validity of job specifications by assessing the level of agreement in ratings and the effects of occupational tenure, occupational complexity, and the abstractness of rated worker requirements. Based on the existing literature, it was hypothesized that (1) agreement will be worse than acceptable levels, (2) agreement will be higher among those with longer tenure, (3) agreement will be lower in more complex occupations, (4) the effect of occupational tenure will be more pronounced in complex than simple occupations, (5) agreement will be higher on more abstract items, and (6) agreement will be lowest for concrete KSAOs in complex occupations. These hypotheses were tested using ratings from 38,041 incumbents in 61 diverse occupations in the Federal government. Consistent with Hypothesis 1, agreement failed to reach acceptable levels in nearly every case, whether measured with the awg or various forms of the rwg agreement indices. However, tenure, occupational complexity, and item abstractness had little effect on ratings, whether agreement was measured with rwg or awg. The most likely explanation for these null findings is that the disagreement reflected a coarse classification system that overshadowed the effects of tenure, complexity, and abstractness. The existence of meaningful subgroups within a single title threatens the content validity of job specifications: the extent to which they include all relevant and predictive KSAOs. Future research must focus on the existence of such subgroups, their consequences, and ways of identifying them. / Ph. D.

The purpose of this study was to determine the critical core occupational competencies for secondary agricultural education programs as identified by Ohio agricultural business and industry. The method used to generate this information was an item analysis of the competencies that industry experts identified as core competencies in the Ohio Competency Analysis Profile (OCAP) process. OCAPs are a source of competencies that agricultural educators use to teach the essential skills needed for employment in agricultural careers. The study identified the importance of and relative time spent on core competencies in 10 agricultural occupations, determined the critical core of occupational competencies in each of 10 agricultural occupations, and determined the common core of critical occupational competencies across all 10 agricultural occupations. A survey of Ohio agricultural business and industry workers was conducted. The competency lists for this study consisted of 10 agricultural education OCAPs developed by the Vocational Instructional Materials Laboratory at The Ohio State University. The OCAP lists consisted of: Agricultural Production, Agricultural Sales and Service, Agricultural/Industrial Mechanical Technician, Animal Management Technician, Floriculture and Greenhouse Worker, Forest Industry Worker, Meat Processor, Nursery and Garden Center Worker, Resource Conservation, and Turf and Landscape Worker. Conclusions included: 1. Competencies in the general safety precautions unit: demonstrate safe work habits, maintain safe work environment, and operate equipment and vehicles were ranked among the 20 most important competencies in all 10 agricultural occupations. 2. One competency in the general safety precautions unit, operate equipment and vehicles, was the only competency ranked among the top 20 competencies on relative time spent in all 10 agricultural occupations. 3. A critical core of occupational competencies was identified for each agricultural occupation. 4. Each agricultural occupation is so highly specialized that a substantial common core of critical occupational competencies in agricultural occupations could not be identified. Selected recommendations included: 1. Given that the competencies in the general safety precautions unit are the most important competencies in all agricultural occupations, agricultural educators should concentrate on preparing workers with general safety precaution competencies. 2. Because a critical core of occupational competencies can be identified, agricultural education programs that need to determine the occupational content for the program should concentrate on the critical core competencies for the occupational focus of that agricultural education program. 3. Because the common core of critical occupational competencies across all 10 agricultural occupations is not substantial, agricultural education programs cannot be generic agricultural education programs with a common core of critical occupational competencies for program content. Agricultural education programs should be occupationally specific. / Ed. D.

Although job analysis is basic to almost all human resource functions, little attention has been given to the response format and scoring strategy of job analysis instruments. This study investigated three approaches to scoring polychotomous and dichotomous responses from the frequency and importance scales of the Common Metric Questionnaire (CMQ). Factor, latent trait, and number endorsed scores were estimated from the responses of 2684 job incumbents in six organizations. Scores from four of the CMQ scales were used in linear and nonlinear multiple regression equations to predict pay. The results demonstrated that: (a) simple number endorsed scoring of dichotomous responses was superior to the other scoring strategies; (b) Scoring of dichotomous responses was superior to scoring of polychotomous responses for each scoring technique; (c) scores estimated from the importance scale were better predictors of pay then scores from the frequency scale; (d) the relationship between latent trait and factor scores is nonlinear; (e) latent trait scores estimated with the two-parameter logistic model were superior to latent trait scores from the three parameter model; (f) test information functions for each scale demonstrated that the CMQ scales accurately measured a relatively narrow range of theta; (g) the reliability of factor scores estimated from dichotomous data is superior to factor scores from polychotomous data. Issues regarding the construction of job analysis instruments and the use of item response theory are discussed. / Ph. D.

Industrial and Organisational Psychology / M. Com. (Industrial and Organisational Psychology )

Industrial and Organisational Psychology / M. Com. (Industrial and Organisational Psychology )