Academic literature on the topic 'Operational performance'

PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO<br>Esta tese aborda o tema de Planejamento de Vendas e Operações, designado pelo acrônimo inglês de SeOP (Sales and Operations Planning). Trata-se de um campo recente em Gerência de Operações. SeOP é definido como um processo interfuncional e integrado de planejamento tático e como um conjunto coeso de práticas gerenciais que unificam diferentes planos de negócios (vendas, marketing, desenvolvimento de novos produtos, manufatura, compras e finanças) em um conjunto de planos integrados internamente e na cadeia de suprimentos, com a finalidade de criar valor e impacto no desempenho das empresas. Objetiva equilibrar oferta e demanda em nível de produtos e famílias de produtos, com um horizonte de planejamento que coincide com o ciclo de planejamento estratégico dos negócios. A eficiência do processo é medida e avaliada para melhoria continua. Compreende um conjunto coeso de práticas gerenciais, direcionado a incentivar o alinhamento horizontal (entre funções) e vertical (do plano de negócios a operações), na empresa e na cadeia de suprimentos. O objetivo da tese é duplo: proceder a uma revisão sistemática e abrangente da literatura em SeOP; avaliar o impacto dos processos e das práticas de SeOP no desempenho operacional da manufatura. A revisão bibliográfica sobre SeOP foi feita a partir das bases de dados eletrônicas EBSCO, Emerald e SCIENDIRECT. Ao todo 271 resumos e 55 textos completos foram revistos e classificados em um quadro conceitual de referência, que relaciona variáveis contextuais, de entrada (inputs), objetivos, estruturas e processos, resultados intermediários e resultados finais do SeOP. Foi constatada a ausência de sínteses anteriores da literatura sobre o tema e uma grande disparidade de conceitos e modelos de maturidade do SeOP, que impossibilitaram a análise estatística dos resultados publicados (meta-análise). Uma síntese sistematizada da literatura foi apresentada. Notou-se igualmente que existem poucos artigos científicos rigorosos que demonstrem o impacto das práticas de S&OP no desempenho das empresas. Ainda mais raros são os estudos empíricos baseados em teorias de gerência de operações. A verificação empírica do impacto das práticas de SeOP interno e de integração na cadeia de suprimentos com fornecedores e com clientes foi realizada com modelos de equações estruturais e de regressão múltipla passo a passo. A base de dados da Pesquisa Internacional de Estratégia da Manufatura (IMSS-V), reagrupando 725 empresas de 34 países foi utilizada na análise. A formulação dos modelos baseou-se na teoria de contingência estrutural. O efeito do SeOP (medido pelo coeficiente de regressão) no desempenho operacional da manufatura foi positivo e consistente para as dimensões da qualidade, flexibilidade e entregas, situando-se no intervalo entre 0,26 e 0,36. Contatou-se igualmente que a integração com fornecedores e as tecnologias de processo na manufatura são moderadoras do impacto no desempenho em todas as dimensões de desempenho e que a tecnologia de produtos modera o desempenho em termos de qualidade. Conclui-se que há uma necessidade de aprofundar a agenda de pesquisas com estudos empíricos baseados em teorias de gerência de operações na manufatura em diferentes contextos e indústrias, de estender e aprofundar a análise do SeOP na cadeia de suprimento, assim como de conduzir estudos de casos. A principal implicação prática do estudo resulta dos fatores contingenciais do impacto do SeOP no desempenho. A indústria ganharia a conduzir processos e práticas de SeOP de forma concomitante com a integração com fornecedores na cadeia de suprimento e a adoção de tecnologias de processo e de produtos que sejam adequadas ao ambiente no qual atua.<br>Sales and Operations Planning (SandOP) is a new and growing research field in Operations Management. The thesis intends to: (i) provide a comprehensive research synthesis of the extant literature on SandOP; and (ii) explore SandOP impact on manufacturing operational performance dimensions of quality, delivery and flexibility, informed by structural contingency theory. A synthesis framework was proposed. Due to disparate concepts and measurements, the field is not yet ripe for meta analysis. There is also a paucity of rigorous empirical research in the impact of SandOP on manufacturing operational performance, anchored in Operations Management theories. Data from 725 metal products and machinery manufacturers (ISIC 3.1, code 28-35) in 34 countries from the fifth round of the International Manufacturing Strategy Survey was used for hypotheses tests. Scales were validated with confirmatory factor analysis and analyzed with stepwise multiple regression. SandOP effect size on quality, delivery and flexibility was on the 0.26 - 0.36 range, after controlling for economic development, market dynamics and firm size. Supply Chain integration with suppliers and manufacturing process technology moderate SandOP impact on all three performance dimensions. Product technology moderates quality but not delivery or flexibility. Misfit of process technology, cross functional team work and product technology adversely affect performance. Practitioners should simultaneously pursue SandOP implementations, integration with suppliers and use of adequate technology to boost performance. Further research should focus on theory validation, case studies and survey research on SandOP.

What operational factors can explain the performance differences between manufacturing firms? Scholars have produced a significant volume of research that examines the linkages between operational factors (resources and practices) and firm performance. There is agreement that organizational capabilities mediate the relationship between operational factors and firm performance. However, due to the numerous and sometimes contradictory definitions of organizational capabilities in the literature and because organizational capabilities includes non-operational factors, it has been suggested that operational capabilities, as a sub construct of organizational capabilities, is more appropriate for establishing an empirical relationship between operational factors and firm performance. Scholars have argued that process improvement practices facilitate the development of operational capabilities, which can consequently lead to improved firm performance. Other scholars have argued that process improvement practices facilitate organizational knowledge creation, which can also influence firm performance. We integrate these two theoretical perspectives into a single conceptual model that better explains the relationship between knowledge-creating practices and firm operational performance. Specifically, we argue that knowledge-creating practices play a significant role in developing a firm’s operational capabilities, which in turn, influence firm operational performance. This research investigates the existence of a relationship between organizational knowledge creation and firm operational performance that is mediated by operational capabilities.

Many power transmission systems are under pressure from increasing load demand as well as changes in power flows due to the evolution of the power market and the integration of renewable energy generations. At the same time, limited finance for installing new cables and the difficulties in reinforcement of existing circuits in urban areas incentivize transmission operators around the world to find ways to maximize the flexibility and usage of their existing transmission network. As a result, it is crucial to adopt new current rating methods which are able to optimize asset utilization, minimize risk and reduce the constraint costs incurred by transmission system operators. Historically, most cable thermal ratings are continuous ratings, with fixed seasonal values for a certain cable circuit. They are based on worst-case assumptions and are not able to consider the real-time environmental conditions. The ignorance of the real-time change in environmental conditions, which control the rate of heat dissipation from the cable, makes continuous ratings generally conservative. However, the rating values can also be optimistic for some extreme situations such as thermal runaway in the soil around the cables, which might cause overheating. Several dynamic rating systems have been applied to the existing underground cable in practice by using online monitoring data. Some worst case assumptions used in conventional cable rating standards have been removed. Such systems have been reported to deliver increases of 5-20% in cable current capacity. However, most existing dynamic rating systems can only determine a short-term rating at the current time step. It would be valuable for transmission operators to know the short-term rating in advance to assist in day-ahead planning. To solve this problem, a predicted rating system, which is capable of providing network operators with accurate short term current ratings at the day ahead stage, has been developed in this work. This novel cable rating concept integrates a day-ahead load forecasting system into the dynamic rating system to provide the time-limited short-term rating calculated forward from any point within the next 24 hours. Some shortcomings of existing rating methods for different kind of insulated cable installations have been detected and overcome. More suitable models have been built, compromising between accuracy and solution speed to fit them into the predicted rating system. A day-ahead load forecasting system has been built by using the Support Vector Regression (SVR) method. Dynamic thermal models are used to translate the load prediction into thermal prediction 24 hours ahead. Thus, the time-limited short-term ratings can then be calculated 24hrs ahead, based on the predicted load data and cable temperature data. In addition, an error estimation system has been integrated to estimate the predicted conductor temperature error quickly, thus increases the reliability of the predicted rating system. Utilizing this predicted rating system has the double benefit of reducing variations in dynamic ratings (which makes them difficult to plan with), while reducing the risk of thermally overloading the cable, thus prematurely ageing the dielectric. For a large scale transmission network, the dynamic rating and predicted rating systems for all the cable circuits might require huge amounts of computation and very long solution times, which make their application impractical and infeasible. The idea of using a machine learning method, such as Support Vector Regression, has been shown to dramatically reduce the solution time for dynamic rating calculations.

Thesis (M.S. in Meteorology and Physical Oceanography)--Naval Postgraduate School, September 2006.<br>Thesis Advisor(s): Tom Murphree, Rebecca Stone. "September 2006." Includes bibliographical references (p. 61-62). Also available in print.

The railway system is a complex network that involves continuous interaction of human operators with technology, procedures and regulations to ensure safe and efficient operations. From an architectural perspective, the complexity of the interactions presents a risk of failure with the consequence that safety incidents and accidents may occur. The common approach to the development of measures for mitigating such occurrences is the retrospective analysis of accidents and incidents; in order firstly to identify, classify and acknowledge the contributing factors and secondly, to suggest mitigation strategies. Research undertaken globally using retrospective analysis indicates that a large number of railway accidents and incidents are associated with human errors due to degraded human performance. In particular, it has been shown that train operators (drivers, signallers and controllers) account for the majority of accidents and incidents. For example, between 1990 and 2009, at least 75% of fatal railway accidents in Europe were due to excessive speed, signal passed at danger or signalling/dispatching errors. There has been a significant research effort to examine, identify and understand the factors that affect human performance in railway operations, so as to prevent conditions related to degrade performance and to reduce the probability of human errors. However current methods, developed on the principles of Human Reliability Analysis (HRA), are based on research from other domains, including nuclear, oil and gas, and aviation. Hence, they are not suited to the rail industry and can be difficult to apply reliably to railway specific operations. Moreover, in the case of the factors that affect human performance, current methodologies have either adopted lists of factors from other domains or slightly modified existing lists, and then applied them to the railway industry. In addition, even in the cases where the lists of factors have been modified, such alterations have been designed on the basis of regional accident and incident analysis. Although the number of factors that influence performance can be claimed to be limited, e.g. fatigue, training, organisational culture and system design, the analysis of only regional occurrences does not provide analysts with a worldwide perspective of the significance of factors on human performance. Therefore, this thesis addresses the current limitations and proposes a new framework to identify the factors that affect the performance of railway operators, and assess human performance. In particular, this thesis developed for the first time a novel and comprehensive taxonomy for railway operations, referred to as the Railway-Performance Shaping Factors (R-PSFs) taxonomy. The taxonomy is derived from a variety of sources including: extensive literature review, operators' hierarchical task analysis, and the analysis of global accidents and incidents. Subject matter experts validated the taxonomy. Results identified 43 contributing factors, whilst further statistical analysis indicates that 12 out of 43 factors are responsible for more than 90% of total occurrences regardless of the type of network, responsibility and severity of consequences. Unlike current taxonomies, the framework developed accounts for both the influence of each individual factor and the dynamic interactive influence of the factors due to their mutual dependencies. It is recommended that the R-PSFs taxonomy be used by railway stakeholders to enhance the Safety Management Systems of their organisation. In addition the taxonomy can be used as part of the training program of the organisations in order to inform and engage the railway personnel with respect to the factors that primarily affect their performance. Finally, the taxonomy is recommended for use by the investigator stakeholders to obtain information about the human aspect that may have led to railway occurrences. This thesis also developed, tested and validated a framework, referred to as the Human Performance (HuPeROI) to enhance safety in railway operations. Based on the 12 largest contributing factors, the HuPeROI is a novel scheme to assess human performance, as function of the various R-PSFs. The HuPeROI for the first time introduces an approach to quantify the impact of each of the factors that affect human performance accounting for all the dependencies amongst those factors. HuPeROI has been developed by integrating the generic concept of two techniques, the Analytic Network Process and the Success Likelihood Index Methodology (SLIM). The former is one of the best known and widely used multi-criteria decision making techniques and was used to evaluate the influence of each R-PSF on operators' performance. SLIM was applied to rate the importance of each of the R-PSFs for different operational actions and finally to estimate the reliability index for these actions. The HuPeROI framework was demonstrated in a case study in three different types of railway operations: regional, high-speed and underground, and helps to define the influence of each individual factor on human performance as well as to indicate the relative likelihoods of different human errors. Finally, both the R-PSFs taxonomy and HuPeROI can be transferred and used with minor modifications not only in other railway procedures, e.g. maintenance, but also domains, e.g. aviation, maritime and oil.

Performance improvement is the natural objective of any intervention in the organisation. Performance improvement in operational terms is particularly interesting when it is able to influence the competitive position of the firm. By being able to deliver superior value and/or offer prices through lower costs a firm will increase customer satisfaction and loyalty and potentially increase its market share and profitability. This research explores the determinants of strategic operational performance improvement, the particular questions we address are: 1) What characterise the process in which the firm achieves operational performance that is strategically significant?, and 2) Why once advantage is achieved, it is not automatically replicated? The manufacturing strategy model and the literature associated with the resource-based theory provide the theoretical foundations of this work, although the link between the two literatures is problematic because their fundamentals are usually at odds. Because the nature of the work is exploratory, and its purpose is one of theory building, we build a model of strategic operational improvement through grounded research. Four case studies are studied and analysed in order to test and improve the model. The results provide a number of insights on the role of managerial rationality, managerial behaviour, and the relationship between managerial and workers behaviour. We are also able to address a number of questions on the nature of strategy in operations. The final product of this thesis is model that relates the processes in the organisation to the firm's initial conditions to explain the evolution of performance. Empirical evidences suggest that the strategic improvement of operational performance depends on the sequence evolution of initial conditions, managerial behaviour, and organisational behaviour. It is argued that by understanding the relationships in this model it is possible to develop more effective operations processes which are able to deliver superior value and or lower costs.

Submitted by Marcia Scarpin (mrs.scarpin@gmail.com) on 2016-06-15T20:33:38Z No. of bitstreams: 1 TESE _2016_MarciaScarpin.pdf: 8479445 bytes, checksum: 6461eb5a2c0335091a054924d454d4c9 (MD5)<br>Approved for entry into archive by Pamela Beltran Tonsa (pamela.tonsa@fgv.br) on 2016-06-16T12:04:40Z (GMT) No. of bitstreams: 1 TESE _2016_MarciaScarpin.pdf: 8479445 bytes, checksum: 6461eb5a2c0335091a054924d454d4c9 (MD5)<br>Made available in DSpace on 2016-06-16T12:11:10Z (GMT). No. of bitstreams: 1 TESE _2016_MarciaScarpin.pdf: 8479445 bytes, checksum: 6461eb5a2c0335091a054924d454d4c9 (MD5) Previous issue date: 2016-04-07<br>Operational capabilities are characterized as an internal resource of the firm and source of competitive advantage. However, the literature of operations management provides inadequate constitutive definitions of operational capabilities, does not cover the relativization to different contexts, has limited empirical grounding, and does not adequately explores the more extensive empirical literature on operational practices. When practices are operationalized in the internal environment of the firm, they can be incorporated as organizational routines, and through the pre-existing tacit knowledge of production, become operational capabilities, thus creating barriers to imitation. But, a few scholars have explored operational practices as an antecedent of operational capabilities. Based on this review, we investigated about nature of operational capability; the relationship between operational practices and operational capabilities; types of operational capabilities characterized in the firm’s internal environment; and the impact of the operational capabilities on operational performance. Therefore, we conduct a mixed methods research. In qualitative stage, we conducted case studies in four firms, two multinational American firms operating in Brazil and two local Brazilian firms. We collected data through semi-structured interviews with open-ended questions, based on our theoretical review of operational practices and operational capabilities. The interviews were conducted face-to-face. In total, 73 interviews were performed in four different firms (21 - first case, 18 - second case, 18 - third case, 16 – fourth case). All interviews were recorded and transcribed literally in NVivo software. In quantitative stage, the sample was composed of 206 firms. The questionnaire creation involved an extensive review of the literature and also the use of the results of the analysis of the qualitative phase data. Q-sort was performed. Pre-test was administered to production managers. Measures were conducted to reduce Common Method Variance. A total of ten scales were used: 1) Continuous Improvement; 2) Information Management; 3) Learning; 4) Customer Support; 5) Innovation; 6) Operational Efficiency; 7) Flexibility; 8) Customization; 9) Supply Management; and 10) Operational Performance. We use Confirmatory Factor Analysis to conducted reliability, content, convergent, and discriminant validity. The data were analyzed using regressions. Our main results were: First, relate the operational practices as an antecedent of operational capabilities. Second, the creation of a typology divided into two constructs. The first construct is called Standalone Capabilities. This group consists of zero order capabilities such as Customer Support, Innovation, Operational Efficiency, Flexibility, Customization, and Supply Management. These capabilities aim to improve operational processes of the firm. They have a direct relationship with operational performance. Second construct is called Across-the-Board Capabilities. It is composed of first order capabilities such as Learning, Continuous Improvement, and Information Management. These capabilities are considered dynamic and they have the role to reconfigure Standalone Capabilities.<br>Operational capabilities são caracterizadas como um recurso interno da firma e fonte de vantagem competitiva. Porém, a literatura de estratégia de operações fornece uma definição constitutiva inadequada para as operational capabilities, desconsiderando a relativização dos diferentes contextos, a limitação da base empírica, e não explorando adequadamente a extensa literatura sobre práticas operacionais. Quando as práticas operacionais são operacionalizadas no ambiente interno da firma, elas podem ser incorporadas as rotinas organizacionais, e através do conhecimento tácito da produção se transformar em operational capabilities, criando assim barreiras à imitação. Apesar disso, poucos são os pesquisadores que exploram as práticas operacionais como antecedentes das operational capabilities. Baseado na revisão da literatura, nós investigamos a natureza das operational capabilities; a relação entre práticas operacionais e operational capabilities; os tipos de operational capabilities que são caracterizadas no ambiente interno da firma; e o impacto das operational capabilities no desempenho operacional. Nós conduzimos uma pesquisa de método misto. Na etapa qualitativa, nós conduzimos estudos de casos múltiplos com quatro firmas, duas multinacionais americanas que operam no Brasil, e duas firmas brasileiras. Nós coletamos os dados através de entrevistas semi-estruturadas com questões semi-abertas. Elas foram baseadas na revisão da literatura sobre práticas operacionais e operational capabilities. As entrevistas foram conduzidas pessoalmente. No total 73 entrevistas foram realizadas (21 no primeiro caso, 18 no segundo caso, 18 no terceiro caso, e 16 no quarto caso). Todas as entrevistas foram gravadas e transcritas literalmente. Nós usamos o sotware NVivo. Na etapa quantitativa, nossa amostra foi composta por 206 firmas. O questionário foi criado a partir de uma extensa revisão da literatura e também a partir dos resultados da fase qualitativa. O método Q-sort foi realizado. Um pré-teste foi conduzido com gerentes de produção. Foram realizadas medidas para reduzir Variância de Método Comum. No total dez escalas foram utilizadas. 1) Melhoria Contínua; 2) Gerenciamento da Informação; 3) Aprendizagem; 4) Suporte ao Cliente; 5) Inovação; 6) Eficiência Operacional; 7) Flexibilidade; 8) Customização; 9) Gerenciamento dos Fornecedores; e 10) Desempenho Operacional. Nós usamos análise fatorial confirmatória para confirmar a validade de confiabilidade, conteúdo, convergente, e discriminante. Os dados foram analisados com o uso de regressões múltiplas. Nossos principais resultados foram: Primeiro, a relação das práticas operacionais como antecedentes das operational capabilities. Segundo, a criação de uma tipologia dividida em dois construtos. O primeiro construto foi chamado de Standalone Capabilities. O grupo consiste de zero order capabilities tais como Suporte ao Cliente, Inovação, Eficiência Operacional, Flexibilidade, e Gerenciamento dos Fornecedores. Estas operational capabilities têm por objetivo melhorar os processos da firma. Elas têm uma relação direta com desempenho operacional. O segundo construto foi chamado de Across-the-Board Capabilities. Ele é composto por first order capabilities tais como Aprendizagem Contínua e Gerenciamento da Informação. Estas operational capabilities são consideradas dinâmicas e possuem o papel de reconfigurar as Standalone Capabilities.

Design co-ordination is aimed at improving the performance of the design development process. It can be viewed as providing the continuous coherent organisation and control of the assignment of inter-related tasks to the most relevant resources such that they can be undertaken and completed in a suitable order in a timely and appropriate manner. The nature of operational design co-ordination is discussed resulting in the identification of key issues, i. e. coherence, communication/interaction, task management, resource management, schedule management and real-time support. Based on these key issues, existing approaches related to operational engineering management have been critically reviewed and found to exhibit a number of fundamental limitations. In addition, aimed at addressing the key issues identified and overcoming the limitations of existing approaches, a set of requirements have been established that define an approach to operational design co-ordination. A novel, integrated and holistic approach to operational design co-ordination has been developed enabling the performance of the design development process to be improved. This approach consists of two components: a methodology and a knowledge modelling formalism. Further, the methodology consists of two parts: real-time and prospective. Real-time operational design co-ordination enables the coherent, timely and appropriate structured undertaking of inter-related tasks while continuously optimising the utilisation of the resources, in accordance with dynamically derived schedules, within a changeable design development process. Prospective operational design co-ordination facilitates the identification of deficiencies in terms of existing resources with respect to scheduled tasks and, thus, the assessment of proposed improvements to the resources. The knowledge modelling formalism of tasks, resources and schedules supports the methodology. Three practical case studies from engineering industry have been used to evaluate the approach. A prototype agent-oriented system, called the Design Co-ordination System, has been developed to evaluate the implementation of the real-time part of the methodology by applying it to a turbine blade design process. The prospective part of the methodology has been applied to practical case studies concerning a marine vessel conversion design programme and a rotary drum dryer design development process. Based on the evaluation of the approach, its strengths and weaknesses have been identified. Finally, areas of possible future work have been recommended to improve the approach and develop the Design Co-ordination System. In addition, based on industrial feedback, further applications of the approach have been suggested.

In recent years there is a rapid increase in demand for cloud services, as cloud computing has become a flexible platform for hosting microservices over the Internet. Microservices are the core elements of service oriented architecture (SOA) that facilitate the deployment of distributed software systems. As the user requires good quality of service the response time of microservices is critical in assessing the performance of the application from the end user perspective.This thesis work aims at developing a typical service architecture to facilitate the deployment of compute and I/O intensive services. The work also aims at evaluating the service times of these service when their respective subservices are deployed in heterogeneous environments with various loads.The research work has been carried out using an experimental testbed in order to evaluate the performance. The transport level performance metric called Response time is measured. It is the time taken by the server to serve the request sent by the client. Experiments have been conducted based on the objectives that are to be achieved.The results obtained from the experimentation contain the average service times of a service when it is deployed on both virtual and non-virtual environment. The virtual environment is provided by Docker containers. They also include the variation in position of their subservices. From results it can be concluded that the total service times obtained are less in case of non-virtual environments when compared to container environment.