The impact of bandwidth in structured interviewing and criterion stability in predicting and assessing manager performance across transition and maintenance stages

The current study examined the role of three important components in the use of structured employment interviewing in performance prediction: construct bandwidth, observed communication skill, and the stability/dynamicity of performance criteria over time. A matched sample of 242 hospitality managers was derived from a field data set provided by a large hospitality management organization. Interview data and two years of performance appraisal data were provided. Bandwidth analysis demonstrated only minimal differences in prediction between matched predictor-criterion pairs compared with predictor to overall aggregate ratings (unmatched). The communication skill analysis revealed that this interviewer rated observation significantly predicted a number of the individual performance dimensions as well as overall performance over time. Of the five interview items, the strongest overall predictor of performance was interviewer rated communication skill. The stability/dynamicity analyses demonstrated the performance criteria to be generally stable over the two year period examined, which provides support for the long held notion that performance criteria is stabile over time. However, there were two exceptions. The interview dimension customer service orientation had shifting relationships over time with four of the criteria over the two year period. The performance criteria employee development also demonstrated some instability in its relationships with predictors. Thus, some evidence of dynamicity in performance criteria was revealed. Interestingly, both of the most noteworthy findings in the study involved items that were rated differently than the others in the study. The rated interview item communication skill and the rated performance criteria client satisfaction were ratings that involved a more direct level of observation. Additional analyses also revealed evidence of a general factor of performance. These two themes are more fully covered in the discussion.

Aspects of the transplantation, storage and maintenance of corals (Montastraea Faveolata, Acropora Cervicornis and A. Palmata)

The purpose of this study is to explore aspects of coral transplantation for restoration. Montastraea faveolata cores of 2.54 and 5.0 cm were stored in aquaria, on an array and on the substrate. Survival on the array and substrate were 100% for 12 and 11 months respectively. Branches of Acropora cervicornis had 75.0 % survival on the substrate and 91.7% on the array. Disease caused mortality for the A. cervicornis and the 2.54 cm cores in the aquaria but not for the 5.0 cm cores. Growth was significantly higher for A. cervicornis and A. palmata branches stored on an array than in an open seawater system. The storage type affected growth patterns of both species. M. faveolata fed three times/week increased in surface area significantly more than those fed once and twice/week. Corals fed once per week significantly increased their polyp density. Corals had intermittent respiration while under sub-aerial conditions.

A decision support framework for infrastructure maintenance investment decision-making

Infrastructure management agencies are facing multiple challenges, including aging infrastructure, reduction in capacity of existing infrastructure, and availability of limited funds. Therefore, decision makers are required to think innovatively and develop inventive ways of using available funds. Maintenance investment decisions are generally made based on physical condition only. It is important to understand that spending money on public infrastructure is synonymous with spending money on people themselves. This also requires consideration of decision parameters, in addition to physical condition, such as strategic importance, socioeconomic contribution and infrastructure utilization. Consideration of multiple decision parameters for infrastructure maintenance investments can be beneficial in case of limited funding. Given this motivation, this dissertation presents a prototype decision support framework to evaluate trade-off, among competing infrastructures, that are candidates for infrastructure maintenance, repair and rehabilitation investments. Decision parameters' performances measured through various factors are combined to determine the integrated state of an infrastructure using Multi-Attribute Utility Theory (MAUT). The integrated state, cost and benefit estimates of probable maintenance actions are utilized alongside expert opinion to develop transition probability and reward matrices for each probable maintenance action for a particular candidate infrastructure. These matrices are then used as an input to the Markov Decision Process (MDP) for the finite-stage dynamic programming model to perform project (candidate)-level analysis to determine optimized maintenance strategies based on reward maximization. The outcomes of project (candidate)-level analysis are then utilized to perform network-level analysis taking the portfolio management approach to determine a suitable portfolio under budgetary constraints. The major decision support outcomes of the prototype framework include performance trend curves, decision logic maps, and a network-level maintenance investment plan for the upcoming years. The framework has been implemented with a set of bridges considered as a network with the assistance of the Pima County DOT, AZ. It is expected that the concept of this prototype framework can help infrastructure management agencies better manage their available funds for maintenance.