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Real Estate Investment Trusts (REITs) are firms that own and manage income producing commercial real estate for the benefit of their shareholders. The three studies in this dissertation explore topics relating to best practices of REIT management and portfolio composition. Managers and investors can use the findings herein to aide in analyzing a REIT’s performance and determining optimal investment policies. Utilizing REIT from SNL Real Estate and CRSP, the first two studies examine the role of international diversification upon performance, technical efficiency, and scale efficiency. The third study utilizes REIT data to examine technical and scale efficiency over a 21 year window and investigates characteristics of the REITs that affect the levels of efficiency. CHAPTER 1 – PROFITABILITY OF REAL ESTATE INVESTMENT TRUST INTERNATIONALIZATION Real Estate Investment Trusts (REITs) in the United States have grown extremely fast in terms of assets and market capitalization since the early 1990’s. As with many industries, U.S. REITs began acquiring foreign properties as their size grew and they needed to seek new investment opportunities. This paper investigates the role of holding foreign assets upon the total return of U.S. based REITs from 1995 through 2010. We find that holding foreign properties in associated with negative relative performance when risk, size, and other common market factors are controlled for. Interestingly, the source of the negative performance is not related to the two largest areas for foreign investment, Europe and Canada. Instead, the negative performance is iii detected when a REIT begins acquiring properties in other global regions such as Latin America and Asia/Pacific. This paper has broad ramifications for REIT investors and managers alike. CHAPTER 2 – EFFECT OF INTERNATIONAL DIVERSIFICATION BY U.S. REAL ESTATE INVESTMENT TRUSTS ON COST EFFICIENCY AND SCALE As U.S. based Real Estate Investment Trusts (REITs) have increased their degree and type of holdings overseas, there has yet to a study that has investigated such activity on the REIT’s measures of cost efficiency and scale. Using data from 2010, Data Envelopment Analysis techniques are used to estimate measures of technical and scale efficiency that are then regressed against measures of international diversification and other controls to measure the impact of this global expansion. It is determined that REITs with foreign holdings are significantly larger than domestic REITs and are correspondingly 96% of foreign investing REITs are operating at decreasing returns to scale. Further almost every measure of foreign diversification is negative and significantly impacting scale efficiency. However, simply being a REIT with foreign holdings did positively and significantly associate with higher levels of technical efficiencies. Thus REITs that expand globally may have some advantages in operational efficiency but lose considerably in terms of scale efficiency by increasing their size as they move cross-border. iv CHAPTER 3 – THE EVOLUTION OF TECHNICAL EFFICIENCY AND ECONOMIES OF SCALE OF REAL ESTATE INVESTMENT TRUSTS Data Envelopment Analysis (DEA) is used to measure technical and scale efficiency of 21 years of Real Estate Investment Trust (REIT) data. This is the longest, most complete dataset ever analyzed in the REIT efficiency literature and as such makes a significant contribution as prior efficiency studies’ data windows end in the early 2000’s at latest. Overall, REITs appear to continue to operate at decreasing returns to scale despite rapid growth in total assets. Further, there is some evidence of improving technical efficiency overtime; however the finding is not strong. In summation, it appears that REITs have not improved on a relative basis despite the rapid growth, a finding that suggests a potential of a high degree of firm competition in the REIT industry. Finally, firm characteristics such as debt utilization, management and advisory structure, and property type specialization are tested for their impact upon technical and scale efficiency.

In a time of strained resources and dynamic environments, the importance of effective and efficient systems is critical. This dissertation was developed to address the need to use feedback from multiple stakeholder groups to define quality and assess an entity’s efficiency at achieving such quality. A decision support model with applicability to diverse domains was introduced to outline the approach. Three phases, (1) quality model development, (2) input-output selection and (3) relative efficiency assessment, captured the essence of the process which also delineates the approach per tool applied. This decision support model was adapted in higher education to assess academic departmental efficiency at achieving stakeholder-relative quality. Phase 1 was accomplished through a three round, Delphi-like study which involved user group refinement. Those results were compared to the criteria of an engineering accreditation body (ABET) to support the model’s validity to capture quality in the College of Engineering & Computer Science, its departments and programs. In Phase 2 the Analytic Hierarchy Process (AHP) was applied to the validated model to quantify the perspective of students, administrators, faculty and employers (SAFE). Using the composite preferences for the collective group (n=74), the model was limited to the top 7 attributes which accounted for about 55% of total preferences. Data corresponding to the resulting variables, referred to as key performance indicators, was collected using various information sources and infused in the data envelopment analysis (DEA) methodology (Phase 3). This process revealed both efficient and inefficient departments while offering transparency of opportunities to maximize quality outputs. Findings validate the potential of the ii Delphi-like, analytic hierarchical, data envelopment analysis approach for administrative decision-making in higher education. However, the availability of more meaningful metrics and data is required to adapt the model for decision making purposes. Several recommendations were included to improve the usability of the decision support model and future research opportunities were identified to extend the analyses inherent and apply the model to alternative areas.

The thesis examines technical efficiency using frontier efficiency estimation techniques from parametric and non-parametric approaches. Five different frontier efficiency estimation techniques are considered which are SFA, DFA, DEA-CCR, DEA-BCC and DEA-RAM. These techniques are then used on an artificially generated panel dataset using a two-input two-output production function framework based on characteristics of German life-insurers. The key contribution of the thesis is firstly, a study that uses simulated panel dataset to estimate frontier efficiency techniques and secondly, a research framework that compares multiple frontier efficiency techniques across parametric and non-parametric approaches in the context of simulated panel data. The findings suggest that, as opposed to previous studies, parametric and non-parametric approaches can both generate comparable technical efficiency scores with simulated data. Moreover, techniques from parametric approaches, i.e. SFA and DFA are consistent with each other whereas the same applies to non-parametric approaches, i.e. DEA models. The research study also discusses some important theoretical and methodological implication of the findings and suggests some ways whereby future research can enable to overcome some of the restrictions associated with current approaches.

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This dissertation investigates two broad management accounting questions in the context of electric utility industry: How do regulators for electricity industry use the information generated from accounting systems to make pricing decisions? What are the economic consequences of these decisions? In Chapter 2, I review regulatory reforms and discuss existing issues of using DEA models for efficiency benchmarking in four aspects. Suggestions are given for improving the use of DEA models based on the review and discussion. In Chapter 3, I empirically investigate the effect of incentive regulation with DEA benchmarking on operational efficiency using a panel of electricity distribution firms in Brazil. In Chapter 4, I examine the effect of restructuring and retail competition on cost reduction using a sample of US investor-owned electric utilities. The effects of privatization, industrial restructuring, incentive regulation and benchmarking are effectively disentangled from one another using the research setting in Brazil and US electricity industry. In Chapter 5, I combine the idea of activity based costing and data envelopment analysis to further develop a detailed benchmarking model for incentive regulation. / Business Administration/Accounting

Determining the best way for evaluating organizational performance is a complex problem as it involves assessment of indicators in multiple dimensions. In the case of nonprofit social service provision this evaluation needs to consider also the outcomes of the service. This research develops a performance measurement system that collects performance indicators, evaluates them and provides concrete performance improvement recommendations to decision-makers in the nonprofit sector. Three dimensions of performance are identified for social services: effectiveness or outcome achievement, service quality and efficiency. A framework for measuring performance in four stages or nodes is advanced. The nodes represent the most important production functions for nonprofit organizations dedicated to social services. These are: (a) financial (fundraising or income generation activities); (b) capacity creation; (c) service delivery; and, (d) effectiveness. Survey instruments were developed to collect service quality and effectiveness indicators for the last two nodes. Effectiveness measures were identified following a well-structured 7-step approach to develop outcome-based objectives. To effectively deal with this problem, the Data Envelopment Analysis (DEA) formulation was adapted to evaluate performance at each node. DEA computes performance scores, optimal target performance levels, and the performance frontier for different branches, units, or other comparable decision-making units (DMUs). Two basic formulations were developed for this framework as follows: Model I as a four stage formulation that carries the actual values of output variables of one node to the successive node, and Model II as a formulation that carries the projections — i.e. the recommended targets' from one node to the other. This last formulation assumes that the DMUs have undergone a reengineering effort and that their indicators are set at their maximum potential. Several environmental factors affecting social service provision were included in the analysis. Additionally, variable selection recommendations were developed for DEA analysis and DEA graphical reports produced. It was concluded that decision makers could use Model I to identify performance improvement targets in each production node. The results from Model II can be used for resource planning after the targets are achieved. Finally, this performance measurement framework is being implemented at one of largest national social service agencies in the United States. / Ph. D.

Highly deteriorated U.S. road infrastructure, major budgetary restrictions and the significant growth in traffic have led to an emerging need for improving efficiency and effectiveness of highway maintenance practices that preserve the road infrastructure so as to better support society's needs. Effectiveness and efficiency are relative terms in which the performance of a production unit or decision making unit (DMU) is compared with a benchmark (best practice). Constructing the benchmark requires making a choice between an "estimation approach" based on observed best practices (i.e., using data from input and output variables corresponding to observed production units (DMUs) to estimate the benchmark with no elaboration on the details of the production process inside the black box) or an "engineering approach" to find the superior blueprint (i.e., focusing on the transformation process inside the black box for a better understanding of the sources of inefficiencies). This research discusses: (i) the application of the estimation approach (non-parametric approach) for evaluating and comparing the performance of different highway maintenance contracting strategies (performance-based contracting versus traditional contracting) and proposes a five-stage meta-frontier and bootstrapping analytical approach to account for the heterogeneity in the DMUs, the resulting bias in the estimated efficiency scores, and the effect of uncontrollable variables; (ii) the application of the engineering approach by developing a dynamic micro-level simulation model for the highway deterioration and renewal processes and its coupling with calibration and optimization to find optimum maintenance policies that can be used as a benchmark for evaluating performance of road authorities. This research also recognizes and discusses the fact that utilization of the maintenance budget and treatments that are performed in a road section in a specific year directly affect the road condition and required maintenance operations in consecutive years. Given this dynamic nature of highway maintenance operations, any "static" efficiency measurement framework that ignores the inter-temporal effects of inputs and managerial decisions in future streams of outputs (i.e., future road conditions) is likely to be inaccurate. This research discusses the importance of developing a dynamic performance measurement framework that takes into account the time interdependence between the input utilization and output realization of a road authority in consecutive periods. Finally, this research provides an overview of the most relevant studies in the literature with respect to evaluating dynamic performance and proposes a classification taxonomy for dynamic performance measurement frameworks according to five issues. These issues account for major sources of the inter-temporal dependence between input and output levels over different time periods and include the following: (i) material and information delays; (ii) inventories; (iii) capital or generally quasi-fixed factors and the related topic of embodied technological change; (iv) adjustment costs; and (v) incremental improvement and learning models (disembodied technological change). In the long-term, this line of research could contribute to a more efficient use of societal resources, greater level of maintenance services, and a highway and roadway system that is not only safe and reliable, but also efficient. / Ph. D.

Affordability of products and services is an economic benefit that should accrue to consumers, whether they are corporations, government agencies or individuals. This concept of affordability goes beyond conventional wisdom that considers affordability as the ability to pay the price of a product or service. This dissertation defines and explores a broader concept of affordability – one of fitness to perform at the level of quality required by the consumer, to perform at that level whenever the product or service is used, and to do so with minimum consumption of resources. This concept of affordability is applied to technological systems by using the complexity sciences concept of fitness as the metaphor for technological systems' fitness. During a system design evolution, the specific design outcome is determined by that set of design search paths followed – it is path dependent. Dynamic mechanisms create, dictate and maintain path dependence. Initial conditions define the start and direction of a path. During subsequent design steps, positive feedback influences the designer to continue on that path. This dissertation describes underlying mechanisms that create, dictate and maintain path dependence; discusses the effects of path dependence on system design and system affordability; models these effects using system dynamics modeling; and suggests actions to address its effects. This dissertation also addresses several types of fitness landscapes, and suggests that the Data Envelopment Analysis (DEA) solution space is a form of fitness landscape suitable for evaluating the efficiency, and thus the fitness, of research and development (R&D) projects. It describes the use of DEA to evaluate and select Department of Defense (D0D) R&D projects as a new application of DEA. / Ph. D.