864 resultados para Process performance


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Data envelopment analysis (DEA) has been proven as an excellent data-oriented efficiency analysis method for comparing decision making units (DMUs) with multiple inputs and multiple outputs. In conventional DEA, it is assumed that the status of each measure is clearly known as either input or output. However, in some situations, a performance measure can play input role for some DMUs and output role for others. Cook and Zhu [Eur. J. Oper. Res. 180 (2007) 692–699] referred to these variables as flexible measures. The paper proposes an alternative model in which each flexible measure is treated as either input or output variable to maximize the technical efficiency of the DMU under evaluation. The main focus of this paper is on the impact that the flexible measures has on the definition of the PPS and the assessment of technical efficiency. An example in UK higher education intuitions shows applicability of the proposed approach.

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Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

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Organizations today face intense competitive and economic pressures leading to large scale transformation of existing business operations and transactions. In addition, organizations have adopted automated business processes to deal with partners and customers. E-business diffusion is a multi-phase process, moving from initiation through to routinisation and an insight into the adoption processes helps organizations to adopt e-business more effectively. It is imperative that organizations effectively manage the e-business environment, and all associated changes to accommodate the changing relationships with customers and business partners and more importantly, to improve performance. This chapter discusses the process of e-business implementation, usage and diffusion (routinisation stage) on business performance. © 2010, IGI Global.

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This paper considers the use of general performance measures in evaluating specific planning and design decisions in higher education and reflects on the students' learning process. Specifically, it concerns the use of the MENTOR multimedia computer aided learning package for helping students learn about OR as part of a general business degree. It includes the transfer of responsibility for a learning module to a new staff member and a change from a single tutor to a system involving multiple tutors. Student satisfaction measures, learning outcome measures and MENTOR usage patterns are examined in monitoring the effects of the changes in course delivery. The results raise some questions about the effectiveness of general performance measures in supporting specific decisions relating to course design and planning.

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This article is a contribution to an emerging scholarship on the role of rhetoric, persona and celebrity, and the effects of performance on the political process. We analyse party leader Ed Miliband at the UK Labour Party Conference in Manchester in 2012. Our analysis identifies how, through performance of himself and the beginnings of the deployment of an alternative party narrative centred on One Nation, Ed Miliband began to revise his received persona. By using a range of rhetorical and other techniques, Miliband began to adapt the Labour narrative to the personalized political. The article sets out the theoretical framework for the analysis and returns to the implications for the theory of leadership performance in its conclusion.

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As workforce diversity increases, knowledge of factors influencing whether cultural diversity results in team performance benefits is of growing importance. Complementing and extending earlier research, we develop and test theory about how achievement setting readily activates team member goal orientations that influence the diversity-performance relationship. In two studies, we identify goal orientation as a moderator of the performance benefits of cultural diversity and team information elaboration as the underlying process. Cultural diversity is more positive for team performance when team members' learning approach orientation is high and performance avoidance orientation is low. This effect is exerted via team information elaboration.

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The Product Service Systems, servitization, and Service Science literature continues to grow as organisations seek to protect and improve their competitive position. The potential of technology applications to deliver service delivery systems facilitated by the ability to make real time decisions based upon ‘in the field’ performance is also significant. Research identifies four key questions to be addressed. Namely: how far along the servitization continuum should the organisation go in a single strategic step? Does the organisation have the structure and infrastructure to support this transition? What level of condition monitoring should it employ? Is the product positioned correctly in the value chain to adopt condition monitoring technology? Strategy consists of three dimensions, namely content, context, and process. The literature relating to PSS, servitization, and strategy all discuss the concepts relative to content and context but none offer a process to deliver an aligned strategy to deliver a service delivery system enabled by condition based management. This paper presents a tested iterative strategy formulation methodology which is the result of a structured development programme.

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The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.

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Time, cost and quality are the prime objectives of any project. Unfortunately, today’s project management does not always ensure the realisation of these objectives. The main reasons of project non-achievement are changes in scope and design, changes in Government policies and regulations, unforeseen inflation, under-estimation and mis-estimation. An overall organisational approach with the application of appropriate management philosophies, tools and techniques can only solve the problem. The present study establishes a methodology for achieving success in implementing projects using a business process re-engineering (BPR) framework. Internal performance characteristics are introspected through condition diagnosis that identifies and prioritises areas of concern requiring attention. Process re-engineering emerges as a most critical area for immediate attention. Project process re-engineering is carried out by eliminating non-value added activities, taking up activities concurrently by applying information systems rigorously and applying risk management techniques throughout the project life cycle. The overall methodology is demonstrated through applications to cross country petroleum pipeline project organisation in an Indian scenario.