Submitted by Sandro Camargo (sandro.camargo@unipampa.edu.br) on 2015-05-09T19:30:37Z No. of bitstreams: 1 117110019.pdf: 3622835 bytes, checksum: bf885e1754a3be10513d615ebdb016c7 (MD5) / Made available in DSpace on 2015-05-09T19:30:37Z (GMT). No. of bitstreams: 1 117110019.pdf: 3622835 bytes, checksum: bf885e1754a3be10513d615ebdb016c7 (MD5) Previous issue date: 2013-11-23 / Este trabalho investiga o processo de evolução dos índices de eficiência técnica e de produtividade de Malmquist para as 30 maiores empresas distribuidoras de energia elétrica no Brasil, confrontando a metodologia do órgão regulador (Agência Nacional de Energia Elétrica – ANEEL) de avaliação dos Custos Operacionais Regulatórios do Ciclo de Revisão Tarifária Periódica, com as relações existentes entre a tecnologia de produção utilizada por estas empresas e a qualidade dos serviços prestados à sociedade, entre 2003 e 2009, aplicando-se a Análise por Envoltória de Dados (Data Envelopment Analysis – DEA). Para tanto, utilizam-se os seguintes modelos DEA, orientados para insumo: o CRS (CCR), o VRS (BCC) e o NDRS (usado pela ANEEL), que presumem tecnologias com os seguintes retornos à escala de produção: constantes, variáveis e não decrescentes, respectivamente. Sendo estes modelos DEA aplicados aos dois cenários modelados: no primeiro (chamado de C1), observam-se as variáveis quantitativas adotadas pela ANEEL, tendo como insumo o Custo Operacional – OPEX (R$) e como produtos a Extensão de Redes de Distribuição de Energia Elétrica – Rede (km), o Consumo de Energia Elétrica – Mercado (TWh) e o Número de Unidades Consumidoras de Energia Elétrica – UC (No de Clientes); no segundo (chamado de C2) são inseridas variáveis de qualidade ao cenário C1, definindo-as como produtos na modelagem DEA, citando-se o Índice ANEEL de Satisfação do Cliente – IASC (No Índice) e o Indicador de Desempenho Global de Continuidade – DGC (No Índice). Desta forma, com base nos resultados de desempenho relativo para o período analisado, identificam-se como resultados principais a tendência de evolução positiva das medidas de eficiência técnica e a tendência de estabilização das medidas de produtividade, para o conjunto das 30 maiores empresas distribuidoras de energia elétrica do país. Além disso, comparando-se os resultados de eficiência técnica e produtividade, nos diferentes cenários e nas diferentes modelagens DEA (benchmarking), verificou-se que a implementação de um cenário e de uma modelagem deve refletir a realidade econômica (aproximação com a função de produção verdadeira) das empresas distribuidoras de energia elétrica no Brasil, de modo a possibilitar a identificação das distribuidoras de energia elétrica que estão operando na escala ótima (ou não) e se os retornos à escala de produção são constantes, crescentes ou decrescentes. Assim, percebeu-se que boa parte das empresas (C1 igual a 40% e C2 igual a 50%) apresentaram retornos de escala de produção decrescentes (DRS) em todo o período de tempo analisado. Portanto, a modelagem DEA VRS apresenta-se mais adequada para a avaliação de desempenho, em detrimento da modelagem DEA NDRS usada pela ANEEL, pois admite que as empresas atuem na região decrescente da fronteira de produção e ainda assim possam ser consideradas eficientes. Já o cenário C2, ao agregar variáveis de qualidade ao Cenário C1 (ANEEL), aproxima-se também desta realidade econômica, buscada pelo órgão regulador através da mensuração dos custos operacionais regulatórios associados aos indicadores de qualidade na prestação dos serviços à comunidade. Por fim, são realizadas considerações sobre a necessidade de aprimoramento de alguns pontos na metodologia utilizada pelo regulador, representando desafios para a garantia de equidade entre a modicidade tarifária e a sustentabilidade das empresas do setor elétrico brasileiro, de modo a garantir-se, efetivamente, o equilíbrio econômico-financeiro nos próximos Ciclos de Revisão Tarifária Periódica. / This work investigates the evolution process of technical efficiency indices and Malmquist productivity for the 30 largest power utilities in Brazil, comparing the methodology of the regulator (ANEEL – National Agency of Electric Energy) of evaluation of Regulatory Operational Costs of the Periodic Tariff Review Cycle, with the relationship etween the production technology used by these companies and the quality of services provided to the society between 2003 and 2009, applying the Data Envelopment Analysis (DEA). For this, it is used the following models DEA – input oriented: CRS (CCR), the VRS (BCC) and the NDRS (used by ANEEL), assume that the following technologies returns to scale production: constants, variables, and nondecreasing, respectively. It was adopted two scenarios: the first (called C1), it was observed quantitative variables adopted by ANEEL, taking as input the Operating Cost – OPEX (R$), and as products the Extension of Distribution Networks Electricity - Network (km), the Consumption of Electricity – Market (TWh) and the Unit Number of Electric Consumers – UC (No of Customers), the second (called C2), and quality variables to the scenario C1 are inserted by defining them as products in modeling DEA, the ANEEL’s index of Customer Satisfaction - IASC (NoIndex) and Performance Indicator of Global Continuity – DGC (No Index). Thus, based on performance results relative to the analysis period, it is identified measures of technical efficiency with positive trend and productivity measures with stabilizing trend for the whole of the 30 largest power utilities in Brazil. Furthermore, comparing the results of technical efficiency and productivity in the different scenarios and different DEA modeling (benchmarking), it was found that the implementation of a scenario and a model should reflect the economic reality (closer to the function of real production) of power utilities in Brazil, in order to facilitate the identification of power utilities that are operating at optimal scale (or not) and returns to scale of production are constant , increasing or decreasing. Thus, it was noticed that most companies (C1 equal to 40% and C2 equal to 50%) showed decreasing returns to scale of production (DRS) throughout the time period analyzed. Therefore, the VRS DEA model appears more suitable for the evaluation of performance, rather than modeling the DEA NDRS used by ANEEL, since it allows companies to act in the decreasing region of production frontier and still can be considered efficient. Finally, we discuss the need to improve some points in the methodology used by the regulator, representing challenges to ensuring equity between low tariffs and sustainability of the Brazilian electricity sector, in order to guarantee effectively the economic-financial balance over the next Periodic Tariff Review Cycle.

本研究以民國75至86年間，新銀行開放設立前已存在之本國舊銀行實際經營資料，利用資料包絡分析法估計成本效率值，並將之分解為純技術效率、規模效率及配置效率。再利用Tobit迴歸分析，以探討開放新銀行設立對本國舊銀行經營效率之影響。 研究結果發現，整體舊銀行投入資源之運用效率，仍有很大的改善空間。此外，成本無效率之來源主要為技術無效率。 考慮其他影響效率之因素後，開放新銀行設立對舊銀行之經營效率具有顯著之正向影響。此結果顯示新銀行設立對舊銀行之經營形成很大的競爭壓力，導致本國舊銀行不論在資源投入、規模調整或資源配置上，皆積極努力地改善。本實證結果與政府希望透過開放新銀行，對經營僵化之國內銀行業加以刺激，以提升舊銀行經營效率之目標相一致。 / This study empirically examines whether opening up the new banks to establish affects various efficiency ratios of Taiwan old banks or not. It uses Data Envelopment Analysis (DEA) to assess cost efficiency, pure technical efficiency, scale efficiency and allocative efficiency based on the Taiwan old banks data from 1986 to 1997. Then, applies the Tobit censored regression model to examine the relationship between opening up the new banks to set up and these efficiency measures. The empirical result shows that the usage efficiency of resource inpute of whole old banks isn't up to the appropriate point, so there is plenty of space for improvement. Besides, cost inefficiency primarily results from technical inefficiency, not allocative inefficiency. After considering other factors of the effects of efficiency, it's obviously positive relationship between opening up the new banks to set up and operating efficiency of old banks. The result shows that these new banks establish put competitive stress on the operation of old banks. So those old banks try hard to improve their resource input, scale adjustment, or resource allocation, etc. This result corresponds with the government's intention to raise the operating efficiency of original banks.

Στην παρούσα μεταπτυχιακή εργασία περιγράφεται η διαδικασία συνδυασμού προβλημάτων Επιχειρησιακής Έρευνας με την μεθοδολογία εύρεσης συγκριτικής αποδοτικότητας (DEA). Αρχικά, παρουσιάζεται μια γενική περιγραφή της μεθόδου DEA και μια συνοπτική επισκόπηση της σχετικής βιβλιογραφίας. Παρουσιάζεται ο τρόπος συνδυασμού της μεθόδου DEA και δύο κλασσικών μοντέλων χωροθέτησης εγκαταστάσεων, του μοντέλου με περιορισμό και του αντίστοιχου μοντέλου χωρίς περιορισμό στην χωρητικότητα. Για την επίτευξη αυτού του στόχου γίνονται οι απαραίτητοι χειρισμοί στην μέθοδο DEA ούτως ώστε να μπορεί να υπολογίζεται η αποδοτικότητα για όλες τις μονάδες λήψης απόφασης ταυτόχρονα – μέθοδος ταυτόχρονης DEA (Simultaneous DEA), εφόσον το κλασσικό μοντέλο βρίσκει την αποδοτικότητα μιας μονάδας λύνοντας μια φορά το γραμμικό πρόβλημα με τους συντελεστές βαρύτητας αυτής της μονάδας. Η λύση του πολυκριτήριου προβλήματος αναδεικνύει την αλληλεπίδραση μεταξύ κόστους και αποδοτικότητας, για τη λήψη απόφασης ανάλογα με τις ανάγκες που μπορεί ενυπάρχουν σε ένα αντίστοιχο πραγματικό πρόβλημα. Στην συνέχεια αναπτύσσεται για πρώτη φορά στη διεθνή βιβλιογραφία μια μεθοδολογία για το συνδυασμό δύο άλλων βασικών προβλημάτων, της κάλυψης και της σύμπτυξης συνόλου, αντίστοιχα, με την μεθοδολογία DEA. Στόχος είναι να μορφοποιηθεί ένα μοντέλο γραμμικού προγραμματισμού έτσι ώστε εκτός από το μέτρο απόφασης του κόστους για την κάλυψη ή σύμπτυξη ενός συνόλου-στόχου, από διαθέσιμα υποσύνολα να ληφθεί υπόψη και η αποδοτικότητα του εκάστοτε υποσυνόλου, η οποία εν τέλει θα επηρεάσει και την συνολική αποδοτικότητα του συνόλου-στόχου. Γίνεται ο συνδυασμός των μεθοδολογιών και αναπτύσσονται μεθοδολογίες πολυκριτήριας ανάλυσης που μπορούν να χρησιμοποιηθούν για την λήψη αποφάσεων που αφορούν την αποδοτική και οικονομική κάλυψη ή σύμπτυξη ενός συνόλου. Για την πιστοποίηση και τη διαπίστωση της λειτουργικότητας των προτεινόμενων μεθοδολογιών αναπτύσσονται παραδείγματα προβλημάτων, τα οποία και επιλύονται επιτυχώς. / In the present thesis, the combination of Operation Research Problems with the Data Envelopment Analysis (DEA) is performed in order to make optimal and efficient decisions. Firstly, a general description of DEA and a breath literature review is presented. Then, we show and test location modeling formulations that utilize data envelopment analysis (DEA) efficiency measures to find optimal and efficient facility location/allocation patterns. In addition, to the authors’ best knowledge, the combinations of DEA with the Set Covering Problem as well as Set Packing Problem are formulated as multiobjective problems, for first time in the literature. The main aim of the proposed models is to make cost-effective and efficient decisions regarding the Set Covering and Packing Problem, respectively. Numerical examples are developed in order to validate and test the novel models. The numerical results of multiobjective analysis demonstrate that the proposed methods are able to successfully find optimal and efficient solutions for real set covering, packing and partitioning problems.

Este trabalho tem por objetivo propor um método eficiente para avaliar gestão de estoque, aplicando conjuntamente a Teoria de Controle Ótimo (OCT), para obter funções de estocagem dinamicamente ótimas, e Análise Envoltória de Dados (DEA), para calcular as eficiências relativas. Tendo em vista esse objetivo foi desenvolvido um modelo integrado DEA-OCT para calcular a eficiência de custo otimizada ao longo do tempo, quando o sistema possui variáveis relacionadas entre si, como no caso de sistemas de controle de estoque, e para analisar produção e demanda (assim como a variável estoque, oriunda dessa relação), estendendo o modelo variacional. Este trabalho aplica o modelo proposto a 647 empresas das Américas do Sul e do Norte, depois faz uma comparação entre Brasil e Chile (países emergentes economicamente), posteriormente focando no setor de comércio, considerando seus sistemas produção-estoque com dados de variáveis contábeis. Os modelos minimizam os custos de produção e de estoque para calcular a eficiência de custo ao longo do tempo. O output (produto, ou variável de saída) é a demanda; o input (insumo, ou variável de entrada) é a produção, e o intermediate (variável intermediária) é o estoque. Seus custos são considerados na função objetivo. É acrescentada uma restrição variacional da OCT para descrever a relação entre demanda, produção e estoque. Em resumo, o modelo é relevante por calcular eficiência prevenindo a possibilidade de obter uma projeção que ignora a relação entre as variáveis, uma vez que essa relação sempre ocorre, na prática, em sistemas de controle de estoque. As principais contribuições são: possibilitar o uso de OCT como a ferramenta de benchmarking DEA no contexto de eficiência dinâmica, estender o modelo DEA variacional de Sengupta (1995), incluindo restrições de modelos mais recentes e possibilitar o cálculo de eficiência quando há relação entre as variáveis. / This work aims to propose an efficient method to evaluate inventory management, jointly applying optimal control theory (OCT), obtaining dynamically optimal production and inventory functions, and data envelopment analysis (DEA), calculating the relative efficiencies. With this objective in mind, it was developed a DEA-OCT integrated model to calculate allocative efficiency optimized over time, when systems have variable with relationship among themselves, like in the case of inventory control systems, and for analyzing production and demand (as the inventory variable obtained from this relationship), extending the variational model. This paper applies the proposed model to 647 companies from South and North America, after that it was made a comparison between Brazil and Chile (economically emerging countries), then focusing on the commercial sector, considering its production-inventory systems and data from accounting variables. The model minimizes the inventory and production costs to calculate the allocative efficiency over time. The output is demand; the input is production, and the intermediate variable is inventory. Their costs are considered in the objective function. A variational constraint OCT is added to describe the relationship among demand, production, and inventory. In summary, the model is relevant to calculate efficiency by preventing the possibility of finding a projection that ignores the relationship among variables, since this relationship always occur in practice in inventory control systems. The main contributions are: using OCT as the benchmarking tool DEA in the context of dynamic efficiency, extending the Sengupta (1995) variational DEA model, including constraints from recent model and making it possible to calculate efficiency when there is a relationship among variables.

[ES] La buena gestión de la atención primaria como puerta de entrada al sistema sanitario condiciona el funcionamiento de la atención especializada y la hospitalización, lo cual repercute directamente sobre la salud de la población. La sostenibilidad del sistema de salud público implica que los servicios de atención primaria sean eficientes. Objetivo Desarrollar un modelo para evaluar la eficiencia en cuanto a actividad realizada y resultados de salud de las unidades funcionales (UF) de atención primaria del Departamento de Salud Valencia Clínico - La Malvarrosa en los años 2015 a 2019. Metodología Se han integrado las bases de datos de la Conselleria de Sanitat Universal i Salut Pública y el Departamento de Salud Valencia Clínico - La Malvarrosa para obtener para cada UF: características de la población asignada, actividad asistencial y recursos humanos de los centros y consultorios de atención primaria. El análisis factorial pone de manifiesto las principales diferencias y similitudes encontradas entre las UF y permite reducir el número de variables utilizadas para elaborar los modelos de evaluación de la eficiencia, de manera que no se pierda poder explicativo, y facilite la interpretación de los resultados. Se ha utilizado el Análisis Envolvente de Datos (DEA) con orientación input y output y rendimientos variables a escala para la evaluación de la eficiencia. Los inputs incluidos han sido las tasas por 10.000 habitantes de: personal facultativo y personal de enfermería (inputs no discrecionales) y coste farmacéutico; como outputs se han incluido las tasas por 10.000 habitantes de: urgencias hospitalarias, consultas externas, derivaciones, hospitalizaciones evitables, mortalidad evitable y el indicador de eficiencia en la prescripción. Urgencias, hospitalizaciones evitables y mortalidad evitables se consideran outputs no deseables. Y como variables exógenas se han incluido el porcentaje de población mayor de 65 y 80 años y un indicador de morbilidad (case-mix). Se han analizado las puntuaciones de eficiencia de cada UF según tres modelos. Todos los modelos incorporan los mismos inputs y diferentes combinaciones de outputs relacionados con: Actividad asistencial (primer modelo), outcomes o resultados de salud (segundo modelo) y actividad asistencial + outcomes (tercer modelo, en el que se incluyen todos los outputs). Cada modelo se analiza con y sin variables exógenas. Resultados Se han evaluado los tres modelos con sus diferentes especificaciones para identificar las diferencias entre ellos y ver cuál de ellos permite diferenciar más claramente la eficiencia de las UF, teniendo en cuenta variables de calidad, y las características de la población. Se ha obtenido la puntuación de eficiencia de cada UF y se han identificado las UF que forman parte de la frontera eficiente del grupo estudiado. Los resultados han mostrado que existen diferencias en las puntuaciones de eficiencia estimadas en función de las variables introducidas como outputs. Determinadas UF se encuentran siempre en la frontera eficiente o muy cerca, mientras que otras UF son siempre ineficientes. Por otra parte, cuando se consideran outputs de actividad asistencial, las puntuaciones de eficiencia de todas las UF mejoran y aumenta el número de UF eficientes. Se detecta que la puntuación de eficiencia de las UF desciende, en general, a lo largo del periodo evaluado. Esta disminución es más pronunciada cuando se incluyen sólo los outputs de actividad. Conclusiones Se han obtenido diferentes resultados en función del modelo utilizado. El DEA permite analizar las ineficiencias de los centros de atención primaria, aunque es necesario identificar los objetivos esperados de las UF, ya que la perspectiva de los análisis influye en los resultados. / [CA] La bona gestió de l'atenció primària com a porta d'entrada al sistema sanitari condiciona el funcionament de l'atenció especialitzada i l'hospitalització, la qual cosa repercuteix directament sobre la salut de la població. La sostenibilitat del sistema de salut públic implica que els serveis d'atenció primària siguen eficients. Objectiu Desenvolupar un model per a avaluar l'eficiència quant a activitat realitzada i resultats de salut de les unitats funcionals (UF) d'atenció primària del Departament de Salut València Clínic - La Malva-rosa en els anys 2015 a 2019. Metodologia S'han integrat les bases de dades de la Conselleria de Sanitat Universal i Salut Pública i el Departament de Salut València Clínic - La Malva-rosa per a obtindre per a cada UF: característiques de la població assignada, activitat assistencial i recursos humans dels centres i consultoris d'atenció primària. L'anàlisi factorial posa de manifest les principals diferències i similituds trobades entre les UF i permet reduir el nombre de variables utilitzades per a elaborar els models d'avaluació de l'eficiència, de manera que no es perda poder explicatiu, i facilite la interpretació dels resultats. S'ha utilitzat l'Anàlisi Envolupant de Dades (DEA) amb orientació input i output i rendiments variables a escala per a l'avaluació de l'eficiència. Els inputs inclosos han sigut les taxes per 10.000 habitants de personal facultatiu i personal d'infermeria (inputs no discrecionals) i cost farmacèutic; com a outputs s'han inclòs les taxes per 10.000 habitants de consultes, urgències hospitalàries, derivacions, hospitalitzacions evitables, mortalitat evitable i l'indicador d'eficiència en la prescripció. Urgències, hospitalitzacions evitables i mortalitat evitables es consideren outputs no desitjables. I com a variables exògenes s'han inclòs el percentatge de població major de 65 i 80 anys i un indicador de morbiditat (case-mix). S'han analitzat les puntuacions d'eficiència de cada UF segons tres models. Tots els models incorporen els mateixos inputs i diferents combinacions d'outputs relacionats amb activitat assistencial (primer model), outcomes o resultats de salut (segon model) i activitat assistencial + outcomes (tercer model, en el qual s'inclouen tots els outputs). Cada model s'analitza amb i sense variables exògenes. Resultats S'han avaluat els tres models amb les seues diferents especificacions per a identificar les diferències entre ells i veure quin d'ells permet diferenciar més clarament l'eficiència de les UF, tenint en compte variables de qualitat, i les característiques de la població. S'ha obtingut la puntuació d'eficiència de cada UF i s'han identificat les UF que formen part de la frontera eficient del grup estudiat. Els resultats han mostrat que existeixen diferències en les puntuacions d'eficiència estimades en funció de les variables introduïdes com a outputs. Determinades UF es troben sempre en la frontera eficient o molt a prop, mentre que unes altres UF són sempre ineficients. D'altra banda, quan es consideren outputs d'activitat assistencial, les puntuacions d'eficiència de totes les UF milloren i augmenta el número d'UF eficients. Es detecta que la puntuació d'eficiència de les UF descendeix, en general, al llarg del període avaluat. Aquesta disminució és més pronunciada quan s'inclouen només els outputs d'activitat. Conclusions S'han obtingut diferents resultats en funció del model utilitzat. El DEA permet analitzar les ineficiències dels centres d'atenció primària, encara que és necessari identificar els objectius esperats de les UF, ja que la perspectiva de les anàlisis influeix en els resultats. / [EN] The proper management of primary healthcare as the gateway to the health system determines the performance of specialised healthcare and hospitalisation, which has a direct impact on the health of the population. The sustainability of the public health system requires the efficiency of primary healthcare services. Objectives To develop a model to evaluate the efficiency in terms of activity and health outcomes of the functional units (FU) of primary healthcare of the Valencia Clínico - La Malvarrosa Health District in the years 2015 to 2019. Methodology The databases of the Conselleria de Sanitat Universal i Salut Pública and the Valencia Clínico - La Malvarrosa Health District have been integrated to obtain for each FU: characteristics of the covered population, healthcare activity and human resources of the primary healthcare centres. The factorial analysis reveals the main differences and similarities found between the FUs and makes it possible to reduce the number of variables used to develop the efficiency evaluation models, so as not to lose explanatory power and to facilitate the interpretation of the results. Data Envelopment Analysis (DEA) with input and output orientation and variable returns to scale has been used to assess the efficiency. The inputs included were the rates per 10,000 inhabitants of: professional and nursing staff (non-discretionary inputs) and pharmaceutical cost; outputs included the rates per 10,000 inhabitants of: consultations, hospital emergencies, referrals, avoidable hospitalisations, avoidable mortality and the prescription efficiency indicator. Emergencies, avoidable hospitalisations and avoidable mortality are considered undesirable outputs. As exogenous variables we have included the percentage of the population over 65 and 80 years old and a morbidity indicator (case-mix). The efficiency scores of each FU have been analysed according to three models. All models incorporate the same inputs and different combinations of outputs related to: healthcare activity (first model), outcomes (second model) and healthcare activity + outcomes (third model, in which all outputs are included). Each model is analysed with and without exogenous variables. Results The three models have been evaluated with their different specifications to identify the differences between them and to see which of them allows the efficiency of the FU to be differentiated more clearly, considering quality variables and the characteristics of the population. The efficiency score of each FU has been obtained and the FUs that form part of the efficient frontier of the group studied have been identified. The results show that there are differences in the estimated efficiency scores depending on the variables introduced as outputs. Certain FUs are always on the efficient frontier or very close to it, while other FUs are always inefficient. On the other hand, when healthcare activity outputs are considered, the efficiency scores of all FUs improve and the number of efficient FUs increases. It is found that the efficiency score of the FU generally decreases over the period under evaluation. This decline is more pronounced when only activity outputs are included. Conclusions Different results have been obtained depending on the model used. The DEA makes it possible to analyse the inefficiencies of primary healthcare centres, although it is necessary to identify the expected objectives of the FU, as the perspective of the analysis influences the results. / González De Julián, S. (2023). Medida de la eficiencia en atención primaria: fronteras eficientes y modelos no paramétricos condicionados [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/196735

關於供應商評選模式的探討與研究，是現今於供應鏈管理中非常重要的議題，而對於國內外供應商評選的相關性研究中，往往只考量供應商本身績效，而缺乏整體性的考量，有鑑於此，當企業在評選供應商時，不僅是針對單一供應商績效的考量，而對於供應商本身上下游廠商的整體績效的考量，也是相當重要的評選因素。本研究運用資料包絡分析法(Data Envelopment Analysis, DEA)與簡易多屬性評等技術(Simple Multi-Attribute Rating, SMART)，以建構較完整的供應商評選模式，協助企業的決策者選擇最適的供應商。 在進行供應商與供應商所屬的供應鏈之績效評估時，利用資料包絡分析法中的交叉模式計算供應商與供應商所屬的供應鏈之平均效率，再藉由平均效率值以排序供應商與供應商所屬的供應鏈之優先順位，但因兩者之順序會產生不一致的情形，利用SMART法中的排序加總法計算兩者之權重值，最後以加總法計算綜合效率值，依據綜合效率值加以排序以評選最適的供應商，而此兩種方法的結合， 則需透過驗證的方式以確定運用之正確性，利用系統動力學(System Dynamics, SD)以建構供應鏈之整體廠商的經營環境，模擬供應鏈整體廠商之績效評估模式，以產生模擬驗證排序，最後再將綜合排序與驗證排序，利用Spearman等級相關係數驗證其相關性，而最終證明兩排序具有高度相關性，也證實本研究所提出的供應商評選模式富有參考價值。 / The research of supplier selection model is a very important issue in supply chain management (SCM). Even though the research on supplier selection is abundant, the most works usually only consider the performance of the supplier. This situation can result in a lack of integral deliberation. Therefore, the decision-maker wants to select his vendor in the company, it is important that the decision-maker not only focus on the business unit but also add to the overall organization of the supply chain. In this paper the Data Envelopment Analysis (DEA) and the Simple Multi-Attribute Rating (SMART) are developed to construct the effective supplier evaluation model depends upon the constituent parts of the supply chain, which may be helpful for selecting the appropriate vendor. When evaluating the performance of the supplier and the supplier’s supply chain, the cross-efficiency model of DEA is applied to compute average efficiency both the supplier and the supply chain. According to average efficiency, we can arrange the priority order that may be have the inconsistent order for the suppliers and their supply chains. The rank sum weighting of SMART is employed to determine the weights of suppliers and their chains and then the weighted method is used to calculate overall efficiency that ranking of the suppliers is obtained. Above of two methods, we must be verify the model. The System Dynamics (SD) is designed to implement the whole components of the supply chain for business environment and simulate the performance model. Based on this performance model, we can acquire a confirmation list. In the end, the Spearman’s rank correlation coefficient is provided to testify the correlation between the overall order and the confirmation list. The result of the statistic analysis is illustrated the strength of the association. The model can be tailored and applied by firms that are making decisions on supplier selection.

我國國立高級中等學校實施校務基金之目的除了提升績效外，尚期以增進各校自籌財源之動力，以減輕政府財政負擔，自2007年起開始實施校務基金後之績效為何?值得進一步探討。 本研究係以資料包絡分析法評估各國立高級中等學校2010年至2012年的經營績效，並運用麥氏指數衡量其跨期效率變動情形，最後以Tobit迴歸分析，探討外在環境變數對校務基金實施績效之影響。實證研究結果如下： 一、總技術效率分析：2010、2011及2012年平均總技術效率值依序為0.712、0.714、0.705，表示各該年度尚有28.8%、28.6%及29.5%的效率改善空間。若將各國立高級中等學校依照類別區分，普通高中平均總技術效率表現最佳，綜合高中的表現比職業學校佳，特教學校最差。 二、純技術效率分析：2010、2011及2012年平均純技術效率值依序為0.768、0.781、0.771，表示各該年度尚有23.2%、21.9%及22.9%的效率改善空間。普通高中平均純效率表現最佳，綜合高中的表現比職業學校佳，特教學校最差。 三、規模效率分析：2010、2011及2012年平均規模效率值依序為0.923、 0.908、0.908，表示各該年度尚有7.7%、9.2%及9.2%的效率改善空間。2010年以職業學校表現最佳，2011年以綜合高中表現最佳，2012年度以普通高中表現最佳。特教學校在三個年度的平均規模效率均為最差。 四、麥氏指數分析：2010至2012年度之總要素生產力變動值均小於1，呈現衰退現象， 2010至2011年度及2011至2012年度二個跨期均呈現衰退。 五、Tobit迴歸分析：除實施校務基金的年限無顯著影響外，學校區位、校舍面積及學校成立年限等三項外在環境對學校的經營績效均具有影響。 / The purpose of national senior high schools in Taiwan implementing National Senior High Schools Operation Fund is not only improving performance, but also enhancing the schools’ self-motivation of the financial resources to reduce the fiscal burden of government. How is the performance of implementing National Senior High Schools Operation Fund since 2007?It is worthy of further study. This study is based on Data Envelopment Analysis to evaluate the operating performance of national senior high schools from 2010 to 2012. In addition, this study uses Malmquist Index to measure the efficiency changes. Finally, Tobit regression analysis is used and tried to find effects of the external environment variables on the implemenetation performance of National Senior High Schools Operation Fund. The findings of this study are as follows: 1.Overall technical efficiency analysis：the average value of the overall technical efficiency is 0.712、0.714、0.705 in sequence of year 2010、2011 and 2012, and it means that the efficiency improvement is 28.8%, 28.6% and 29.5% each year. If we evaluate the performance of national senior high schools by category, the general high schools are the best, the comprehensive high schools are better than vocational high schools, and the special education schools are the worst. 2.Pure technical efficiency analysis.：the average value of the pure technical efficiency is 0.768、0.781、0.771 in sequence of year 2010、2011 and 2012, and it means that the efficiency improvement is 23.2%、21.9% and 22.9% each year. The general senior high schools are the best, the comprehensive senior high schools are better than vocational senior high schools, and the special education schools are the worst. 3.Scale efficiency analysis: the average value of the scale efficiency is 0.923、 0.908、0.908 in sequence of year 2010、2011 and 2012,and it means that the efficiency improvement is 7.7%、9.2% and 9.2% each year. The best performance is the vocational senior high schools in 2010, the comprehensive senior high schools in 2011, and the general senior high schools in 2012, the special education schools are the worst in all three years. 4.Malmquist Index analysis: the value of the total factor productivity change is totally less than 1 from 2010 to 2012, and shows the recession .And the inter-temporal total factor productivity changes show the recession from 2010 to 2011, and 2011 to 2012. 5.Tobit regression analysis: there is no significant impact in the factor of the years of the National Senior High Schools Operation Fund, but the external factors such as the size, the history, and the location of the schools, would affect the performance of national senior high schools.

本研究透過個案研究，運用資料包絡分析法(DEA)的評估方式，分析製藥業在不同生命週期及通路上資源分配之行銷策略與銷售績效之關聯性。研究結果發現： 一、不同生命週期「成長期」、「成熟期」及「衰退期」產品，其整體銷售技術效率、純銷售技術效率與銷售規模效率之差異，均達統計上之顯著水準。「成長期」產品效率值最差、「成熟期」產品效率值次之、「衰退期」產品效率值最佳。 二、不同生命週期產品在主要銷售通路醫學中心、醫院、診所與藥房的銷售比重不同。「成長期」與「成熟期」產品的主要銷售通路均在醫學中心，而「衰退期」產品的主要銷售通路在藥房。其銷售績效差異在醫學中心與藥房通路，衰退期產品與成熟期、或成長期產品比較，均達到統計上之顯著差異水準，但在醫院與診所通路的銷售績效，三類產品族群的差異就不明顯。 三、個案藥廠對其主要銷售的藥品，雖然都有非常明確的個別產品銷售策略與目標，但差額變數分析結果顯示，仍有部份產品在資源分配及運用上，可以加以改善以提高銷售績效。 / This research is conducted using Data Envelope Analysis (DEA) assessment method to analyze the particular pharmaceutical company on the association between marketing strategy and sales performance with different life-cycle products and sales channels. The results are as follows: 1.Sales performance appears significant differences among different life-cycle products with respect to the overall technical efficiency、pure technical efficiency and scale efficiency. The results revealed that products in「Growth Stage」had the worst efficiency performances, 「Maturity Stage」products placed the second, and「Decline Stage」products were the best. 2.Sales weight differs from different life-cycle products in the major sales channels of medical centers, hospitals, general practitioners and drug stores. The main sales channel of「Growth Stage」and「Maturity Stage」products are in medical centers；while「Decline Stage」products are in drug stores. Statistics showed that the sales performance differed substantially when the three different life-cycle products were distributed to sell in medical centers and drug stores; however, the results were not as evident in hospitals and general practitioners channels. 3.Although the case pharmaceutical company has very clear sales strategies and goals for its individual products, the analytical results showed some changes could be made to improve sales performance.

本論文對於醫療市場的生產績效研究，係由兩篇獨立的學術研究報告所組成，研究重點在於利用非參數資料包絡分析方法 ( nonparametric DEA approach )，估計醫院的生產技術，以衡量醫院的技術效率及不同年度間之生產力變動，進而分析不同醫院間，生產績效差異的主要原因。本論文所採用的研究方法與探討的主題，不同於國內既有的相關文獻。 第一部分：生產不確定性與醫院效率 本部分主要探討在醫院面對不確定性時的效率評估。一般而言，醫院有兩種生產上的不確定性來源：醫師或醫院的診療結果所導致的生產不確定性；及消費者對醫療服務需求的不確定性 (Arrow, 1963)。當醫院面對生產不確定性時，醫院效率將與廠商如何處理不確定性問題有關，亦即，當廠商事前規劃愈縝密，未來可能的產出失靈水準愈低，則其生產效率表現愈佳。本文利用民國 82 及 83 年（準）醫學中心與（準）區域醫院資料，模擬醫院在面對生產不確定性時，各種可能的產出失靈水準，以chance constrained DEA 模式 (Land, Lovell and Thore, 1993) 估算醫院的隨機技術效率，並與傳統、確定性的DEA模式所得到之結果，做一比較。 Chance constrained DEA模式與傳統DEA模式的不同，在於前者估計出的生產前緣，並不總是包絡所有的樣本點，亦即，允許某廠商之產出超越生產前緣或說允許產出失靈可能性之存在，而後者則否。實證結果發現，在chance constrained DEA模式下，私立醫院的技術效率高於公立醫院，且呈現統計顯著性的差異，但兩者間的差異隨著醫院事前準備程度的提高而縮小；而傳統DEA模式也顯示，私立醫院的技術效率確實顯著地高於公立醫院。此外，若產出失靈水準夠低，則chance constrained DEA模式的效率值與傳統DEA模式的效率值，兩者間的分配會呈現統計顯著性差異。 在面對生產不確定性時，欲提升公立醫院的生產效率，應提高廠商事先規劃的程度，才能與私立醫院之生產效率並駕齊驅。一般而言，廠商事先準備的程度高低，與醫院本身的特性有關，因此，欲改善公立醫院緩衝產能的準備程度，以降低產出失靈水準，有必要進行體制層面的改革，亦即，從進行人事變革、財務之授權與彈性化等方向開始做起，如此應可提高公立醫院的生產效率。 第二部分：全民健康保險制度與醫院生產力變動 全民健保實施後，民眾對醫療服務的可近性提高，醫院間的市場結構改變，因此，醫院生產力與效率的提升，成為眾所關切的焦點。為瞭解醫院在全民健保實施後，資源是否有效配置，本部分利用民國 82 至 86 年醫學中心、區域醫院與地區醫院等大小型醫院資料，以範疇DEA模式估計Malmquist生產力變動指標，並將之分解為技術變動、純技術效率變動、及規模效率變動等三項變動來源。 實證結果發現，從82至86年醫院整體平均效率而言，CRS（VRS）生產技術下的平均效率為 66.00%（74.87%），表示不論大小型醫院，平均而言，皆存在技術不效率的情形。再者，在民國84年，亦即全民健保實施的年度，其效率水準明顯較其他年度為低，其餘年度的效率水準都相對較高，此一結果意謂，政策干擾對於醫院效率表現的影響，是短期性的。另外，小型醫院皆較大型醫院不效率，兩者的效率差異呈現統計顯著性；以權屬別而言，不論是大型醫院或小型醫院中的私立醫院，其生產效率均優於公立醫院，且兩者的效率差異呈現統計顯著性。而透過迴歸分析顯示，全民健保實施、權屬別之虛擬變數、佔床率、平均住院日、及以醫院產出衡量的集中度指標等，是影響醫院生產效率的重要因素。 從Malmquist生產力變動（　et al., 1994）來看，平均而言，82-86年間醫院生產力成長率約在 -3.06 % 左右。就生產力變動來源而言，技術成長率（-2.74 %）與整體效率成長率（-0.33 %）均為負，而技術變動則是阻礙生產力成長的主要原因。此外，若以醫院整體效率變動來源來看，平均而言，整體效率退步是由於規模效率變動所致（-0.74%）。 此外，本文著重在　et al.(1994)、Ray and Desli (1997) 及Grifell and Lovell (1998) 三種定義下的Malmquist生產力變動指標之比較。研究結果發現，Grifell and Lovell (1998) 的一般化Malmquist生產力指數，並沒有正確衡量廠商的生產力變動及其變動來源項。而利用Kruskal-Wallis檢定結果發現，三個模式中的生產力變動差異，並不具統計顯著性，而變動來源項（技術變動與規模效率變動）亦顯示相同的結果。 / This dissertation is focused on the efficiency and productivity studies of hospitals in Taiwan. It includes two independent academic papers. The primary intention is to introduce the newly developed ideas in the measurement of efficiency and productivity, rather than to create new ones. The utilization of these ideas has not, however, been discussion in print. And some of the arguments we used and brought together are new regarding to the literature of hospital efficiency and productivity measurement. Utilizing the non-parametric data envelopment analysis (DEA) approaches, efficiency scores and productivity change indexes were estimated. Efforts were made to explain the difference of productivity performance among individual hospitals. Nevertheless, the methods we used and the economic approach behind them distinguish this study from other empirical studies of the medical market. Part I　 Market Uncertainty and Hospital Efficiency This part of the dissertation is focused on the measurement of efficiency of hospitals, incorporating uncertainty. There are stochastic variations in production relationships for hospitals. Generally speaking, the uncertainty of hospitals comes from two major sources: the natural uncertainty of medical cares; and the uncertainty of demands for medical cares (Arrow, 1963). Given the uncertainty in the medical market, the efficiency of hospitals hinges on how decision-makers deal with it. Undoubtedly, an optimal planning of the output buffers improves the efficiency performance. Using the hospital survey data in 1993 and 1994, and employing the chance constrained DEA model (Land, Lovell and Thore, 1993), the stochastic efficiency indexes of public and private medical centers and regional hospitals were estimated. Compared with deterministic frontier enveloping a given set of sample observations all the time, the chance-constrained frontier envelops them most of the time. That is, the chance constrained DEA allows the possibilities of output failure. Imposing different values of output failure probability, the estimation results were compared with the traditional (deterministic) DEA models. The empirical evidences of the chance constrained DEA model showed that, on average, private hospitals performed significantly better than public hospitals. This result matches with the result of the traditional DEA model. With Mann-Whitney U test, we compared the distributions of efficiency indexes under chance constrained DEA and deterministic DEA models. The test results showed that the difference between these two different models is statistically significant given a higher probability of output failure. These results imply that the nature of risk and the manipulation for risk are different for public and private hospitals. We also find that that the efficiency performance of public hospitals could be improved by the increasing of its reserve capacity. Part II　 National Health Insurance and Hospital Productivity Change In this part of the dissertation, we examine the impact of NHI on hospitals, and trace the sources of hospital productivity growth in Taiwan. To pursue our goal, we employ a data consisting of 157 medical centers, regional hospitals and district hospitals over the period 1993 to 1997, and resort to the Malmquist productivity index to measure total factor productivity change. The index could be decomposed into three components: technical change, pure technical efficiency change and scale efficiency change. The estimation technique used in the study is the deterministic non-parametric DEA approach. The results we find are revealing and suggestive to the public and the government in order to promote and assure the efficient delivery of quality health care. The average efficiency scores are 66.00% (74.87%) for CRS (VRS) technology and it means that there are substantial efficiency losses for the sample hospitals during the study period. The efficiency score of the hospitals as a whole in 1995 (the beginning year of NHI) was much lower than the other 4 years' efficiency scores. A censored Tobit regression analysis is used and identifies that NHI policy, ownership, rate of bed occupancy, average length of stay and the output-specific concentration level were all the significant determinants of technical efficiency. Empirical results indicate that most medical care regions became more output-specific concentrated. Total factor productivity on average deteriorated at an annual rate of -3.1%, and it was dominated by substantial technical regresses at an annual rate of -2.74%. The small hospitals were severely affected by NHI. Furthermore, within large and small hospital groups, the difference in technical change was statistically significant, but the differences in TFP and the associated components between ownership were not. Special attention was paid to compare　 et al.(1994), Ray and Desli (1997) and Grifell and Lovell (1998) approaches to decomposing the Malmquist productivity index. Empirical results indicate that the first 2 approaches yield accurate productivity changes, while GL doesn't. However, they produce almost the same magnitude of average TFP. In addition, no significant differences in the measured technical change and efficiency change were found among the three approaches.