1,721,014 research outputs found
Explorative data analysis and Catanova for ordinal variables: an integrated approach
No full textCategorical analysis of variance (CATANOVA) is a statistical method designed to analyse variability between treatments of interest to the researcher. There are well-established links between CATANOVA and the τ statistic of Goodman and Kruskal which, for the purpose of the graphical identification of this variation, is partitioned using singular value decomposition for Non-Symmetrical Correspondence Analysis (NSCA) (D'Ambra & Lauro, 1989). The aim of this paper is to show a decomposition of the Between Sum of Squares (BSS), measured both in CATANOVA framework and in the statistic τ, into location, dispersion and higher order components. This decomposition has been developed using Emerson's orthogonal polynomials. Starting from this decomposition, a statistical test and a confidence circle have been calculated for each component and for each modality in which the BSS was decomposed, respectively. A Customer Satisfaction study has been considered to explain the methodology
Customer satisfaction evaluation by common component and specific weight analysis using a mixed coding system
No full textA statistical model for evaluating the patient satisfaction
No full textThe paper aims to identify the drivers which affect the patient satisfaction. For this purpose the authors analyzed
the data collected by delivering a questionnaire to patients hospitalizing in an important hospital of Napoli city.
The effects of level of satisfaction about different services received in the hospital on the patient satisfaction
have been studied by comparing the results of four regression models. Findings provide empirical evidence that a
policy aimed at developing the competences and the abilities of the staff and at maintaining high standards of
hygiene and cleanliness is the most appropriate strategy to improve patient satisfaction
Restricted Common Component and Specific Weight Analysis: A Constrained Explorative Approach for the Customer Satisfaction Evaluation
No full textServqual is a service measurement multidimensional model (Parasuraman et al. in J Mark 49(4):41–50, 1985; Parasuraman et al. in J Retail 64:12–40, 1988) which involves a set of five dimensions representing service quality. It is based on a questionnaire to measure the gaps between customers’ expectations and perceptions of service. A re-examination and extension of this model, named Servperf, is instead based only on the perceptions (Taylor in J Mark 56(3):55–68, 1992; Taylor in J Mark 58:125–131, 1994). Common Components and Specific Weights Analysis (Qannari et al. in Food Qual Prefer 11:151–154, 2000) (CCSWA) is a useful tool to analyze customer satisfaction evaluation data. The rationale behind this method is the existence of a common structure to the data tables. Therefore, it determines a common space of representation for all data. Each table, which represents a ServPerf dimension, assesses a specific weight to each dimension of the common space. Customer satisfaction can be then investigated with respect to a common reference system where all the dimensions contribute to forming it. Sometimes we may have additional knowledge about some relationships among the service variables that can be incorporated in the analysis as external information. The aim of this paper is then to provide an extension of CCSWA based on an objective function which takes directly into account the external information (as linear constraints). This extension may lead to a simpler interpretation of the analysis results and to explore new relationships. A student satisfaction evaluation study highlights this hypothesis
Analyzing Customer Requirements to Select a Suitable Service Configuration Both for Users and for Company Provider
No full textThe analysis of Customer Satisfaction is an important tool in planning business activities. It allows firms to identify which features and attributes are important for their services or products. In this paper we define nine possible scenarios for a public train trans- port, by means of design of experiments. Each scenario is identified by some quality fac- tors with 3 possible levels. Our aim is to select the scenario that maximizes the satisfaction of potential users. To define the levels composing the best feasible scenario we propose to use Cumulative Correspondence Analysis (by Taguchi method) and the Likelihood Ratio in the logistic regression model. It is also suggested a suitable scenario both for users and company provider
Cumulative Correspondence Analysis as a tool for optimize factor setting in public transport
No full textIn public transport an improvement of the customer satisfaction can attract
further users and individual transport would be used less. Most studies of customer satisfaction deal with ordered categorical data. The aim of this paper is
to propose Cumulative correspondence analysis as a tool to develop a procedure
for choosing the optimal categorical response in a multifactor state system. We
briefly review the cumulative correspondence analysis and the Taguchi’s statistic
and by a case study, recording the choice of the best scenario for a train service,
we illustrate the proposed approach
The evaluation of passenger satisfaction in the local public transport: a strategy for data analysis
No full textThe diffusion of ISO 9001:2000 certification and adoption of mobility char- ter led the companies of Local Public Transport (LPT) to carry out surveys of Passenger Satisfaction (PS). However, often, the data analysis is limited to the application of descriptive and explorative statistical techniques. In this way, the collected data are used in an inefficient way and the information that is transferred to the company management is not sufficient to make decisions.
A good analysis strategy requires the use of a combination of parametric and nonparametric techniques. In this paper we propose the combined appli- cation of Rasch Analysis and Simple Components analysis based on the RV coefficient (SCA-RV)
Cytogenetic and developmental toxicity of cerium and lanthanum to sea urchin embryos.
No full textThe aim of this study was to evaluate the toxicity of two rare earth elements (REE), cerium and lanthanum on sea urchin embryos and sperm. Sea urchin (Paracentrotus lividus) embryos were reared for 72 h in Ce(IV)- or La(III)-contaminated seawater at concentrations ranging from 10(-8) to 10(-5) M. Cleaving embryos (5h post-fertilization) were submitted to cytogenetic analysis, scoring mitotic activity and a set of mitotic aberrations. Embryological analysis was carried out to determine percent developmental anomalies and/or embryonic mortality. P. lividus sperm were suspended in Ce(IV) or La(III) (10(-8)-10(-5)M) for 1h, and percent fertilized eggs were scored in cleaving embryos that were cultured up to pluteus stage to score any developmental defects. Embryos reared in 10(-5)M Ce(IV) resulted in 100% embryonic mortality, whereas 10(-5)M La(III) induced 100% developmental defects, without causing any embryonic mortality. A significant concentration-related mitotoxic effect and induction of mitotic aberrations were observed in Ce(IV)-exposed, but not in La(III)-exposed embryos, at concentrations ranging from 10(-7)M to 3 x 10(-6)M. Following sperm exposure, both Ce(IV) and La(III) induced a decrease in sperm fertilization success at the highest tested concentration (10(-5)M). The offspring of Ce(IV)-exposed, but not of La(III)-exposed sperm displayed a significant concentration-related increase in developmental defects. The results may suggest adverse impacts in REE-exposed biota and warrant further studies of a more extended REE series
Cumulative correspondence analysis to improve the public train transport
Full text linkTo a company, improving customer satisfaction (CS) is a strategic element to increase market share, for example in public transport a growth of users implies a positive effect as private transport reduced.Consequently, the use of statistical methods directed to the analysis of CS is very important to get information necessary to support strategic decisions. In this paper, through Taguchi method for design of experiment, we set nine different hypothetic public train transport (called scenarios) and we asked to potential users to evaluate them by an ordinal scale. In order to analyse this data we use an integrated approach based on Cumulative Correspondence Analysis and the Taguchi's index, it allows to find a scenario that maximizes the satisfaction of potential users
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