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.

Implications of FIN 46 for Accruals Quality and Investment Efficiency

The Financial Accounting Standards Board (FASB) issued Interpretation No. 46 (FIN 46), Consolidation of Variable Interest Entities – An Interpretation of ARB No. 51, in January 2003 and revised it in December 2003, with the objective to improve the transparency of financial information. Under FIN 46, companies are required to consolidate variable interest entities (VIEs) on financial statements if they are the primary beneficiaries of the VIEs. This dissertation empirically examines whether the implementation of this new financial reporting guidance affects firms’ accruals quality and investment efficiency. A manually collected sample comprised of firms affected by FIN 46 and firms disclosing no material impact from FIN 46 is used in the empirical analyses.The first part of the dissertation investigates the effects of FIN 46 on accruals quality. By using different accrual quality measures in prior studies, this study found that firms affected by FIN 46 experienced a decrease in accrual quality compared to firms reporting no material impact from FIN 46. Among the firms affected by FIN 46, firms consolidating VIEs were compared with firms terminating or restructuring VIEs. The accruals quality of firms consolidating VIEs was found to be lower than that of firms terminating or restructuring VIEs. These results are consistent in tests using alternative control samples.The second part of this dissertation examines the effects of FIN 46 on investment efficiency. Mixed results were found from using two different proxies used in prior literature. Using the investment-cash flow sensitivity to proxy for investment efficiency, firms affected by FIN 46 experienced a decrease in investment efficiency compared to firms reporting no material impact. It was also found that higher investment-cash flow sensitivity for firms consolidating VIEs during post-FIN 46 periods compared to both the no-impact firms and the matched pair control sample. Contrasting results were found when the deviation from expected investment is used as another proxy for investment efficiency. Empirical analyses show that FIN 46 firms experienced improved investment efficiency measured by the deviation from expected investment after their adoption of FIN 46. This study also provides explanations for the opposite results from the two different proxies.