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.

Esta dissertaÃÃo busca analisar as diferenÃas tecnolÃgicas da produÃÃo agropecuÃria entre os municÃpios situados nas grandes regiÃes brasileiras, com enfoque especial para o Nordeste brasileiro. Como aporte metodolÃgico, utilizou-se o modelo de meta-fronteira tecnolÃgica proposta por Battese, Rao e OâDonnell (2004) e OâDonnell, Rao e Battese (2008), para responder atà que ponto essas diferenÃas regionais influenciam na eficiÃncia da produÃÃo e qual os seus impactos nos municÃpios. A anÃlise foi dividida em dois modelos. No Modelo 1 propÃs-se analisar e identificar as diferenÃas tecnolÃgicas da produÃÃo agropecuÃria entre os municÃpios situados nas grandes regiÃes brasileiras, exceto pela regiÃo Norte, por questÃes metodolÃgicas. Jà o Modelo 2 voltou-se à diferenciaÃÃo tecnolÃgica da produÃÃo agropecuÃria existente no semiÃrido e no nÃo-semiÃrido do Nordeste. A hipÃtese assumida nesta pesquisa à a existÃncia de um processo de heterogeneizaÃÃo tecnolÃgica do meio rural brasileiro e que esta diferenciaÃÃo impacta no nÃvel de eficiÃncia tÃcnica da produÃÃo agropecuÃria nas diferentes regiÃes do Brasil e mesmo dentro de uma mesma regiÃo. Detectou-se que esta hipÃtese se mostrou verdadeira para os dois Modelos. O Modelo 1 indicou que a tecnologia de produÃÃo agropecuÃria praticadas nos municÃpios situados nas regiÃes Sul e Centro-Oeste sÃo mais avanÃadas. Jà em relaÃÃo ao Modelo 2, os resultados indicaram que, quando comparadas as duas regiÃes, o nÃo-semiÃrido possui a maior eficiÃncia tÃcnica mÃdia em referÃncia à meta-fronteira. / This thesis analyzes the technological differences in agricultural production between municipalities located in the great Brazilian regions, with a special attention on the Brazilian Northeast. As methodological support was utilized the meta-frontier model, proposed by Battese, Rao and OâDonnell (2004) and OâDonnell, Rao and Battese (2008) to answer how these regional differences influence the efficiency of production and like this spatial heterogeneity impacts on municipalitiesâ technical efficiency (TE). The analysis was divided into two models. The first one proposes to analyze and identify the technological differences in agricultural production between the municipalities located in the Brazilian regions, except in the North region, for methodological reasons. On the other hand, the second one searches for the technological differentiation of agricultural production in the semi-arid and non-semiarid regions of the Northeast. For present thesis, the hypothesisis is the existence of a process of technological heterogenization of the Brazilian rural production and that this differentiation affects the level of TE of agricultural production between different regions of Brazil and within the same region as well. It was found that this hypothesis proved to be true for both models. The Model 1 revealed that the production technology practiced in the municipalities located in the South and Center-West regions are more advanced. Regarding the Model 2 indicated that the non-semiarid has the highest average TE with reference to the meta-frontier, when compared to the semiarid region.

Sociotechnical systems (STSs) rely on the collaboration between humans and autonomous decision-making units to fulfill their objectives. Highly intertwined social and technical contextual factors influence the collaboration between these human and engineered elements, and consequently the performance characteristics of the STS. In the next two decades, the role allocated to STSs in our society will drastically increase. Thus, the effective design of STSs requires an improved understanding of the human-autonomy interdependency. This dissertation brings together management science along with systems thinking and uses a mixed-methods approach to investigate the interdependencies between people and the autonomous systems they collaborate within complex socio-technical enterprises. The dissertation is organized in three mutually exclusive essays, each investigating a distinct facet of STSs: safe management, collaboration, and efficiency measurement. The first essay investigates the amount of work allocated to safety-critical decision makers and quantifies Rasmussen's workload boundary that represents the limit of attainable workload. The major contribution of this study is to quantify the qualitative theoretical construct of the workload boundary through a Pareto-Koopmans frontier. This frontier allows one to capture the aggregate impact of the social and technical factors that originate from operational conditions on workload. The second essay studies how teams of humans and their autonomous partners share work, given their subjective preferences and contextual operational conditions. This study presents a novel integration of machine learning algorithms in an efficiency measurement framework to understand the influence of contextual factors. The results demonstrate that autonomous units successfully handle relatively simple operational conditions, while complex operational conditions require both workers and their autonomous counterparts to collaborate towards common objectives. The third essay explores the complementary and contrasting roles of efficiency measurement approaches that deal with the influence of contextual factors and their sensitivity to sample size. The results are organized in a structured taxonomy of their fundamental assumptions, limitations, mathematical structure, sensitivity to sample size, and their practical usefulness. To summarize, this dissertation provides an interdisciplinary and pragmatic research approach that benefits from the strengths of both theoretical and data-driven empirical approaches. Broader impacts of this dissertation are disseminated among the literatures of systems engineering, operations research, management science, and mechanical design. / Doctor of Philosophy / A system is an integrated set of elements that achieve a purpose or goal. An autonomous system (ADS) is an engineered element that often substitutes for a human decision-maker, such as in the case of an autonomous vehicle. Sociotechnical systems (STSs) are systems that involve the collaboration of a human decision-maker with an ADS to fulfill their objectives. Historically, STSs have been used primarily for handling safety critical tasks, such as management of nuclear power plants. By design, STSs rely heavily on a collaboration between humans and ADS decision-makers. Therefore, the overall characteristics of a STS, such as system safety, performance, or reliability; is fully dependent on human decisions. The problem with that is that people are independent entities, who can be influenced by operational conditions. Unlike their engineered counterparts, people can be cognitively challenged, tired, or distracted, and consequently make mistakes. The current dependency on human decisions, incentivize business owners and engineers alike to increase the level of automation in engineered systems. This allows them to reduce operational costs, increase performance, and minimize human errors. However, the recent commercial aircraft accidents (e.g., Boeing 737-MAX) have indicated that increasing the level of automation is not always the best strategy. Given that increasing technological capabilities will spread the adoption of STSs, vast majority of existing jobs will either be fully replaced by an ADS or will change from a manual set-up into a STS. Therefore, we need a better understanding of the relationships between social (human) and engineered elements. This dissertation, brings together management science with systems thinking to investigate the dependencies between people and the autonomous systems they collaborate within complex socio-technical enterprises. The dissertation is organized in three mutually exclusive essays, each investigating a distinct facet of STSs: safe management, collaboration, and efficiency measurement. The first essay investigates the amount of work handled by safety-critical decision makers in STSs. Primary contribution of this study is to use an analytic method to quantify the amount of work a person could safely handle within a STSs. This method also allows to capture the aggregate impact of the social and technical factors that originate from operational conditions on workload. The second essay studies how teams of humans and their autonomous partners share work, given their preferences and operational conditions. This study presents a novel integration of machine learning algorithms to understand operational influences that propel a human-decision maker to handle the work manually or delegate it to ADSs. The results demonstrate that autonomous units successfully handle simple operational conditions. More complex conditions require both workers and their autonomous counterparts to collaborate towards common objectives. The third essay explores the complementary and contrasting roles of data-driven analytical management approaches that deal with the operational factors and investigates their sensitivity to sample size. The results are organized based on their fundamental assumptions, limitations, mathematical structure, sensitivity to sample size, and their practical usefulness. To summarize, this dissertation provides an interdisciplinary and pragmatic research approach that benefits from the strengths of both theoretical and data-driven empirical approaches. Broader impacts of this dissertation are disseminated among the literatures of systems engineering, operations research, management science, and mechanical design.

隨著台海兩岸經貿往來密切，發展迅速，客觀上對銀行業提出了許多服務要求，為兩岸金融業的合作提供了廣闊的空間。本文通過採用數據包絡分析法和共同邊界成本函數比較分析了兩岸商業銀行的成本結構及效率差異，實證結果表示大陸商業銀行的成本效率要高於台灣銀行。對這一結果的可能性解釋是大陸銀行的資產規模要遠高於台灣銀行。銀行總資產越高，其獲取低投入要素價格的市場能力越強，因此生產成本更低，成本效率更高。台灣和大陸商業銀行有必要發揮自身的優勢，通過各種方式和渠道，加快兩岸銀行界合作的進程。 / With cross-strait rapid economic development and trade exchanges, huge business investments have induced a great demand for financial services and provided a broad space for cross-strait cooperation. This paper adopts data envelopment analysis and meta-frontier cost function to compare and analyze the different cost structure and efficiency of mainland and Taiwan commercial banks. The empirical results reveal that cost efficiency of mainland commercial banks is higher than Taiwanese ones, which is maybe caused by the larger bank size and total assets. The larger the size of banks, the higher the market power for reaping the benefits of low input prices, thereby resulting in a lower cost of production and a higher cost efficiency. It is necessary for mainland and Taiwan commercial banks to develop their own strengths to accelerate the process of cross-strait cooperation in the banking sector through various means and channels.

過去文獻大多使用Lerner指數來衡量銀行業之市場競爭度，但在計算過程中有可能出現其值為負之問題。為解決上述問題，本文運用關聯結構函數建立聯立隨機邊界模型，它由銀行成本邊界與兩條產出價格邊界所組成，可以同時衡量放款市場及投資市場之市場競爭度與成本效率。另外，為比較西歐五個國家的銀行市場競爭度與成本效率，本文進一步採用Huang et al. (2014)所提出的新隨機共同邊界模型，此模型除使用共同成本邊界計算技術缺口比率外，還透過產出價格共同邊界衡量潛在Lerner指數，進一步拆解成Lerner指數與MC gap ratio (MCGR)兩部分，可以比較不同國家間的市場競爭程度。 / This paper proposes the copula-based simultaneous stochastic frontier model (CSSFM), composed of a cost frontier and two output price frontiers for the banking sector, in order to measure cost efficiency and market power in the markets of loans and investments. The new Lerner index can be estimated by relying on the simultaneous equations model, consisting of three frontier equations, which avoids obtaining negative measures of the Lerner index. We then apply the new meta-frontier model to simultaneously estimate and compare cost efficiency and market power across five countries over the period 1998-2010. The salient feature of our proposed approach is that it allows for calculating the technology gap ratio on the basis of the cost frontier, as well as evaluating the potential Lerner index from price frontiers, which can be decomposed into the country-specific Lerner index and marginal cost gap ratio.

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