883 resultados para Evaluation criteria


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Articular cartilage has poor reparative capacities, and once damaged cartilage lesions remain chronic and can lead to osteoarthritis. Over the last decade, several innovative therapies have been introduced to promote the regeneration of articular cartilage while sustaining sufficient mechanical stress and permitting a pain free motion. An important measure of outcome is the morphological characterization of the repair tissue in order to allow for cross-study evaluation. The International Cartilage Repair Society has developed a analogue visual scale to quantify repair tissue, which is described in this paper.

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"Sponsored by Office of Policy Development and Research, Department of Housing and Urban Development."

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The purpose of this paper is to examine consumers' experience of a performing arts service to identify the predictors of audience behaviour especially as related to positive repurchase intention. Experiential service settings such as the performing arts have been cited in recent research as service contexts that may challenge current theory that repurchase intention is driven by service quality and customer satisfaction. It is posited that consumer emotions and the hedonic nature of the consumption experience may complicate the evaluation process to repurchase intention in a setting such as the performing arts. Qualitative semi-structured indepth interviews were undertaken of twenty-six performing arts consumers using a pool of questions and prompts developed from a review of the extant literature. Transcribed field notes were examined for key words and phrases and data was divided into the main emergent themes related to each of the questions and also coded for confirmation and is-confirmation of the extant literature constructs and relationships. The dimensions of service experience,price, service quality, target goal-directed emotions and non-target appraisal emotions were identified as driving repurchase intention in a performing arts setting. Customer satisfaction in this setting appears to result from emotional factors rather than expectancy dis-confirmation. This research supports the notion that an experiential consumption experience such as the performing arts will challenge the current theory of the drivers of repurchase intention and suggests that a more thorough large scale examination of these dimensions in this service setting is warranted.

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Building construction is a highly competitive and risky business. This competitiveness is compounded where conflicting objectives amongst contracting and subcontracting firms set the stage for an adversarial and potentially destructive business relationship. Clients, especially those from the public sector, need broader tender evaluation criteria to complement the traditional focus on bid price. There is also a need for change in the construction industry—not only to a more cooperative approach between the constructing parties—but also from a confrontationist attitude to a more harmonious relationship between all stakeholders in providing constructed facilities. A strategic alliance is a cooperative relationship between two or more organisations that forms part of their overall strategies, and contributes to achieving their major goals and objectives. Strategic alliances in building construction may provide a useful tool to assist public sector construction managers evaluate tenders and concurrently encourage more cooperative relationships amongst construction stakeholders. This paper begins with an overview of the Australian building construction industry, then reviews the existing strategic alliance literature and describes an analysis framework comprising six attributes of strategic alliances for application to construction organisations—trust, commitment, interdependence, cooperation, communication, and joint problem solving. These attributes are currently being used to collect data from 70 building construction firms in Queensland to assess their respective levels of strategic alliance. Given the trend towards broader indicators of construction firm performance, these attributes are proposed as a tool for use in the tender evaluation process for public works.

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The two-phrase best-value process has been widely used by public agencies for Design and Build (DB) procurement, with a key issue in the first phase of pre-qualification being the determination of evaluation criteria. This study identified a set of general qualification criteria for design-builders and compares their relative importance by a thorough content analysis of 97 Requests for Qualification (RFQ) for public DB projects advertised between 2000 and 2011 in various regions of the USA. The thirty-nine qualification criteria found are summarized and classified into eight categories comprising: experience; project understanding and approach; organizational structure and capacity; past performance record; professional qualifications; responsiveness to RFQs, office location and familiarity with local environment; and legal status in descending order of their relative importance. A comparative analysis of different types of projects shows that the relative weightings of the qualification criteria vary according to different characteristics of the DB projects involved.

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The design-build (DB) system has been demonstrated as an effective delivery method and has gained popularity worldwide. However it is observed that a number of operational variations of DB system have emerged since the last decade to cater for different client’s requirements. After the client decides to procure his project through the DB system, he still has to choose an appropriate configuration to deliver their projects optimally. However, there is little research on the selection of DB operational variations. One of the main reasons for this is the lack of evaluation criteria for determining the appropriateness of each operational variation. To obtain such criteria, a three-round Delphi survey has been conducted with 20 construction experts in the People’s Republic of China (PRC). Seven top selection criteria were identified. These are: (1) availability of competent design-builders; (2) client’s capabilities; (3) project complexity; (4) client’s control of project; (5) early commencement & short duration; (6) reduced responsibility or involvement; and (7) clearly defined end user’s requirements. These selection criteria were found to have a statistically significant agreement. These findings may furnish various stakeholders, DB clients in particular, with better insight to understand and compare the different operational variations of the DB system.

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Existing compliance management frameworks (CMFs) offer a multitude of compliance management capabilities that makes difficult for enterprises to decide on the suitability of a framework. Making a decision on the suitability requires a deep understanding of the functionalities of a framework. Gaining such an understanding is a difficult task which, in turn, requires specialised tools and methodologies for evaluation. Current compliance research lacks such tools and methodologies for evaluating CMFs. This paper reports a methodological evaluation of existing CMFs based on a pre-defined evaluation criteria. Our evaluation highlights what existing CMFs offer, and what they cannot. Also, it underpins various open questions and discusses the challenges in this direction.

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This study attempts to provide a criteria-based approach that can be used to evaluate the potential for technology transfer and commercialisation of a new technology from university research. More specifically, this study offers the critical factors for assessing marketability and feasibility of an innovation for the commercialisation and technology transfer process. The Delphi technique has been used to refine and categorise assessment criteria identified from various models and frameworks that emerged from literature. Proposed categories of criteria that are found to be important in the evaluation and assessment of a new technology for the commercialisation purpose include: Technological Readiness; Legal and Regulatory; Social Benefits and Impact; Economic and Market Factors.

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In each stage of product development, we need to take decisions, by evaluating multiple product alternatives based on multiple criteria. Classical evaluation methods like weighted objectives method assumes certainty about information available during product development. However, designers often must evaluate under uncertainty. Often the likely performance, cost or environmental impacts of a product proposal could be estimated only with certain confidence, which may vary from one proposal to another. In such situations, the classical approaches to evaluation can give misleading results. There is a need for a method that can aid in decision making by supporting quantitative comparison of alternatives to identify the most promising alternative, under uncertain information about the alternatives. A method called confidence weighted objectives method is developed to compare the whole life cycle of product proposals using multiple evaluation criteria under various levels of uncertainty with non crisp values. It estimates the overall worth of proposal and confidence on the estimate, enabling deferment of decision making when decisions cannot be made using current information available.

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The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

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Various research fields, like organic agricultural research, are dedicated to solving real-world problems and contributing to sustainable development. Therefore, systems research and the application of interdisciplinary and transdisciplinary approaches are increasingly endorsed. However, research performance depends not only on self-conception, but also on framework conditions of the scientific system, which are not always of benefit to such research fields. Recently, science and its framework conditions have been under increasing scrutiny as regards their ability to serve societal benefit. This provides opportunities for (organic) agricultural research to engage in the development of a research system that will serve its needs. This article focuses on possible strategies for facilitating a balanced research evaluation that recognises scientific quality as well as societal relevance and applicability. These strategies are (a) to strengthen the general support for evaluation beyond scientific impact, and (b) to provide accessible data for such evaluations. Synergies of interest are found between open access movements and research communities focusing on global challenges and sustainability. As both are committed to increasing the societal benefit of science, they may support evaluation criteria such as knowledge production and dissemination tailored to societal needs, and the use of open access. Additional synergies exist between all those who scrutinise current research evaluation systems for their ability to serve scientific quality, which is also a precondition for societal benefit. Here, digital communication technologies provide opportunities to increase effectiveness, transparency, fairness and plurality in the dissemination of scientific results, quality assurance and reputation. Furthermore, funders may support transdisciplinary approaches and open access and improve data availability for evaluation beyond scientific impact. If they begin to use current research information systems that include societal impact data while reducing the requirements for narrative reports, documentation burdens on researchers may be relieved, with the funders themselves acting as data providers for researchers, institutions and tailored dissemination beyond academia.

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The purpose of this paper is to present two multi-criteria decision-making models, including an Analytic Hierarchy Process (AHP) model and an Analytic Network Process (ANP) model for the assessment of deconstruction plans and to make a comparison between the two models with an experimental case study. Deconstruction planning is under pressure to reduce operation costs, adverse environmental impacts and duration, in the meanwhile to improve productivity and safety in accordance with structure characteristics, site conditions and past experiences. To achieve these targets in deconstruction projects, there is an impending need to develop a formal procedure for contractors to select a most appropriate deconstruction plan. Because numbers of factors influence the selection of deconstruction techniques, engineers definitely need effective tools to conduct the selection process. In this regard, multi-criteria decision-making methods such as AHP have been adopted to effectively support deconstruction technique selection in previous researches. in which it has been proved that AHP method can help decision-makers to make informed decisions on deconstruction technique selection based on a sound technical framework. In this paper, the authors present the application and comparison of two decision-making models including the AHP model and the ANP model for deconstruction plan assessment. The paper concludes that both AHP and ANP are viable and capable tools for deconstruction plan assessment under the same set of evaluation criteria. However, although the ANP can measure relationship among selection criteria and their sub-criteria, which is normally ignored in the AHP, the authors also indicate that whether the ANP model can provide a more accurate result should be examined in further research.