962 resultados para Operations Research


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Cover title.

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Recent research in the non-profit performing arts has shown that marketing efforts designed to increase revenue from ticket sales are not achieving the results required to sustain the performing arts. This paper applies operations management analytical techniques to the non-profit performing arts to increase understanding of operational issues and inform service management strategy. The paper takes a two-study idiographic approach. Implementing a modified version of service transaction analysis (STA), Study One describes a performing arts service from provider and customer perspectives, identifies service gaps and develops an elaborated service description incorporating both perspectives. In Study Two, building on the elaborated service description and extant research, in-depth interviews are conducted to gather thick descriptions of predictors of satisfaction, value and service quality as they relate to repurchase intention (RI). Technical, functional and critical factors required to improve organizational performance are identified. Implications for operational strategy, service design and service management theory for this context are discussed. (c) 2005 Published by Elsevier B.V.

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This paper examines trends in the practice of Operations Management and in teaching the field in major Business Schools. Operations Management has been defined as the design and management of transformation processes that create value for society. The operations function is the one function directly involved in that transformation, and hence is directly responsible for the activities that justify the existence of the firm, both economically and as a value-creating organization in society. The top rated schools in Operations Management are the top-rated research-intensive Business Schools in the world. Operations Management is an area that has been undergoing rapid change in response to changes in business practices worldwide. It is at the heart of changes of which the AACSB report Management Education at Risk, August 2002 (p 20), comments of Business Schools in general: â˜With regard to global relevance (of Business Schools), the complex opportunities and challenges that emanate from the world scope of operations, outsourcing, supply chains, partnerships, and financial and consumer markets â all linked in real time through the Internet â are not reflected adequately in curricula and learning approaches.â Products, and even services, depend increasingly on advanced technology. This is true globally and especially so for countries in South East and East Asia, from which Australian Universities draw a significant number of students. Services operations management has become much more important, while there are both educational and industrial needs in management science or operations research.

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Purpose â This paper aims to present a framework that will help manufacturing firms to configure their internal production and support operations to enable effective and efficient delivery of products and their closely associated services. Design/methodology/approach â First, the key definitions and literature sources directly associated with servitization of manufacturing are established. Then, a theoretical framework that categorises the key characteristics of a manufacturer's operations strategy is developed and this is populated using both evidence from the extant literature and empirical data. Findings â The framework captures a set of operations principles, structures and processes that can guide a manufacturer in the delivery of product-centric servitized offering. These are illustrated and contrasted against operations that deliver purely product (production operations) and those which deliver purely services (services operations). Research limitations/implications â The work is based on a review of the literature supported by data collected from an exploratory case study. Whilst it provides an essential platform, further research will be needed to validate the framework. Originality/value â The principal contribution of this paper is a framework that captures the key characteristics of operations for product-centric servitized manufacture.

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Despite having generated a growing body of literature the subject of international operations is only vaguely defined and lacks any common and accepted frameworks. The aim of this paper is to introduce some clarity into the arena by examining international operations from the perspective of the body of research, the content of some seminal texts, and the practical considerations of firms that have set up and are managing operations in foreign countries. Research output in International Operations is analysed using a model, the dimensions of which have been identified from the core literature and cases of industrial companies. The analysis highlights the range of problems and issues that have been of interest to the community involved in International Operations research and teaching.

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The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfeâs decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

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This study focuses on empirical investigations and seeks implications by utilizing three different methodologies to test various aspects of trader behavior. The first methodology utilizes Prospect Theory to determine trader behavior during periods of extreme wealth contracting periods. Secondly, a threshold model to examine the sentiment variable is formulated and thirdly a study is made of the contagion effect and trader behavior. The connection between consumers' sense of financial well-being or sentiment and stock market performance has been studied at length. However, without data on actual versus experimental performance, implications based on this relationship are meaningless. The empirical agenda included examining a proprietary file of daily trader activities over a five-year period. Overall, during periods of extreme wealth altering conditions, traders "satisfice" rather than choose the "best" alternative. A trader's degree of loss aversion depends on his/her prior investment performance. A model that explains the behavior of traders during periods of turmoil is developed. Prospect Theory and the data file influenced the design of the model. Additional research included testing a model that permitted the data to signal the crisis through a threshold model. The third empirical study sought to investigate the existence of contagion caused by declining global wealth effects using evidence from the mining industry in Canada. Contagion, where a financial crisis begins locally and subsequently spreads elsewhere, has been studied in terms of correlations among similar regions. The results provide support for Prospect Theory in two out of the three empirical studies. The dissertation emphasizes the need for specifying precise, testable models of investors' expectations by providing tools to identify paradoxical behavior patterns. True enhancements in this field must include empirical research utilizing reliable data sources to mitigate data mining problems and allow researchers to distinguish between expectations-based and risk-based explanations of behavior. Through this type of research, it may be possible to systematically exploit "irrational" market behavior.

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The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfeâs decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

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<p>This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing. </p><p>The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability. </p><p>The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.</p><p>Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.</p>

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Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

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In this paper an alternative approach to the one in Henze (1986) is proposed for deriving the odd moments of the skew-normal distribution considered in Azzalini (1985). The approach is based on a Pascal type triangle, which seems to greatly simplify moments computation. Moreover, it is shown that the likelihood equation for estimating the asymmetry parameter in such model is generated as orthogonal functions to the sample vector. As a consequence, conditions for a unique solution of the likelihood equation are established, which seem to hold in more general setting.

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This paper deals with the traditional permutation flow shop scheduling problem with the objective of minimizing mean flowtime, therefore reducing in-process inventory. A new heuristic method is proposed for the scheduling problem solution. The proposed heuristic is compared with the best one considered in the literature. Experimental results show that the new heuristic provides better solutions regarding both the solution quality and computational effort.

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There are several tools in the literature that support innovation in organizations. Some of the most cited are the so-called technology roadmapping methods, also known as TRM. However, these methods are designed primarily for organizations that adopt the market pull strategy of technology-product integration. Organizations that adopt the technology push integration strategy are neglected in the literature. Furthermore, with the advent of open innovation, it is possible to note the need to consider the adoption of partnerships in the innovation process. Thus, this study proposes a method of technology roadmapping, identified as method for technology push (MTP), applicable to organizations that adopt the technology push integration strategy, such as SMEs and independent research centers in an open-innovation environment. The method was developed through action-research and was assessed from two analytical standpoints: externally, via a specific literature review on its theoretical contributions, and internally, through the analysis of potential users` perceptions on the feasibility of applying MTP. The results indicate both the unique character of the method and its perceived implementation feasibility. Future research is suggested in order to validate the method in different types of organizations (C) 2011 Elsevier Ltd. All rights reserved.

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In the last decades, the air traffic system has been changing to adapt itself to new social demands, mainly the safe growth of worldwide traffic capacity. Those changes are ruled by the Communication, Navigation, Surveillance/Air Traffic Management (CNS/ATM) paradigm, based on digital communication technologies (mainly satellites) as a way of improving communication, surveillance, navigation and air traffic management services. However, CNS/ATM poses new challenges and needs, mainly related to the safety assessment process. In face of these new challenges, and considering the main characteristics of the CNS/ATM, a methodology is proposed at this work by combining ""absolute"" and ""relative"" safety assessment methods adopted by the International Civil Aviation Organization (ICAO) in ICAO Doc.9689 [14], using Fluid Stochastic Petri Nets (FSPN) as the modeling formalism, and compares the safety metrics estimated from the simulation of both the proposed (in analysis) and the legacy system models. To demonstrate its usefulness, the proposed methodology was applied to the ""Automatic Dependent Surveillance-Broadcasting"" (ADS-B) based air traffic control system. As conclusions, the proposed methodology assured to assess CNS/ATM system safety properties, in which FSPN formalism provides important modeling capabilities, and discrete event simulation allowing the estimation of the desired safety metric. (C) 2011 Elsevier Ltd. All rights reserved.

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An efficient expert system for the power transformer condition assessment is presented in this paper. Through the application of Duval`s triangle and the method of the gas ratios a first assessment of the transformer condition is obtained in the form of a dissolved gas analysis (DGA) diagnosis according IEC 60599. As a second step, a knowledge mining procedure is performed, by conducting surveys whose results are fed into a first Type-2 Fuzzy Logic System (T2-FLS), in order to initially evaluate the condition of the equipment taking only the results of dissolved gas analysis into account. The output of this first T2-FLS is used as the input of a second T2-FLS, which additionally weighs up the condition of the paper-oil system. The output of this last T2-FLS is given in terms of words easily understandable by the maintenance personnel. The proposed assessing methodology has been validated for several cases of transformers in service. (C) 2010 Elsevier Ltd. All rights reserved.