The role of discriminant analysis in the refinement of customer satisfaction assessment

OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatie...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	BD Verdessi [verfasserIn] G Jara [verfasserIn] R Fuentes [verfasserIn] JC Gonzalez [verfasserIn] F Espejo [verfasserIn] AC de Azevedo [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch ; Spanisch ; Portugiesisch

Erschienen:	2000

Schlagwörter:	Análise discriminante Satisfação dos consumidores Satisfação do paciente Gestão de qualidade total Garantia de qualidade dos cuidados de saúde Controle da qualidade Qualidade dos cuidados de saúde

Übergeordnetes Werk:	In: Revista de Saúde Pública - Universidade de São Paulo, 2004, 34(2000), 6, Seite 623-630
Übergeordnetes Werk:	volume:34 ; year:2000 ; number:6 ; pages:623-630

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1590/s0034-89102000000600010

Katalog-ID:	DOAJ02992216X

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spelling	10.1590/s0034-89102000000600010 doi (DE-627)DOAJ02992216X (DE-599)DOAJbfc221a27fef42e693f401bc72c9fa72 DE-627 ger DE-627 rakwb eng spa por RA1-1270 BD Verdessi verfasserin aut The role of discriminant analysis in the refinement of customer satisfaction assessment 2000 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one. Análise discriminante Satisfação dos consumidores Satisfação do paciente Gestão de qualidade total Garantia de qualidade dos cuidados de saúde Controle da qualidade Qualidade dos cuidados de saúde Public aspects of medicine G Jara verfasserin aut R Fuentes verfasserin aut JC Gonzalez verfasserin aut F Espejo verfasserin aut AC de Azevedo verfasserin aut In Revista de Saúde Pública Universidade de São Paulo, 2004 34(2000), 6, Seite 623-630 (DE-627)324824793 (DE-600)2031055-9 15188787 nnns volume:34 year:2000 number:6 pages:623-630 https://doi.org/10.1590/s0034-89102000000600010 kostenfrei https://doaj.org/article/bfc221a27fef42e693f401bc72c9fa72 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102000000600010&lng=en&tlng=en kostenfrei https://doaj.org/toc/1518-8787 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 34 2000 6 623-630
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allfieldsGer	10.1590/s0034-89102000000600010 doi (DE-627)DOAJ02992216X (DE-599)DOAJbfc221a27fef42e693f401bc72c9fa72 DE-627 ger DE-627 rakwb eng spa por RA1-1270 BD Verdessi verfasserin aut The role of discriminant analysis in the refinement of customer satisfaction assessment 2000 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one. Análise discriminante Satisfação dos consumidores Satisfação do paciente Gestão de qualidade total Garantia de qualidade dos cuidados de saúde Controle da qualidade Qualidade dos cuidados de saúde Public aspects of medicine G Jara verfasserin aut R Fuentes verfasserin aut JC Gonzalez verfasserin aut F Espejo verfasserin aut AC de Azevedo verfasserin aut In Revista de Saúde Pública Universidade de São Paulo, 2004 34(2000), 6, Seite 623-630 (DE-627)324824793 (DE-600)2031055-9 15188787 nnns volume:34 year:2000 number:6 pages:623-630 https://doi.org/10.1590/s0034-89102000000600010 kostenfrei https://doaj.org/article/bfc221a27fef42e693f401bc72c9fa72 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102000000600010&lng=en&tlng=en kostenfrei https://doaj.org/toc/1518-8787 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 34 2000 6 623-630
allfieldsSound	10.1590/s0034-89102000000600010 doi (DE-627)DOAJ02992216X (DE-599)DOAJbfc221a27fef42e693f401bc72c9fa72 DE-627 ger DE-627 rakwb eng spa por RA1-1270 BD Verdessi verfasserin aut The role of discriminant analysis in the refinement of customer satisfaction assessment 2000 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one. Análise discriminante Satisfação dos consumidores Satisfação do paciente Gestão de qualidade total Garantia de qualidade dos cuidados de saúde Controle da qualidade Qualidade dos cuidados de saúde Public aspects of medicine G Jara verfasserin aut R Fuentes verfasserin aut JC Gonzalez verfasserin aut F Espejo verfasserin aut AC de Azevedo verfasserin aut In Revista de Saúde Pública Universidade de São Paulo, 2004 34(2000), 6, Seite 623-630 (DE-627)324824793 (DE-600)2031055-9 15188787 nnns volume:34 year:2000 number:6 pages:623-630 https://doi.org/10.1590/s0034-89102000000600010 kostenfrei https://doaj.org/article/bfc221a27fef42e693f401bc72c9fa72 kostenfrei http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102000000600010&lng=en&tlng=en kostenfrei https://doaj.org/toc/1518-8787 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 34 2000 6 623-630
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In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). 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topic_title	RA1-1270 The role of discriminant analysis in the refinement of customer satisfaction assessment Análise discriminante Satisfação dos consumidores Satisfação do paciente Gestão de qualidade total Garantia de qualidade dos cuidados de saúde Controle da qualidade Qualidade dos cuidados de saúde
topic	misc RA1-1270 misc Análise discriminante misc Satisfação dos consumidores misc Satisfação do paciente misc Gestão de qualidade total misc Garantia de qualidade dos cuidados de saúde misc Controle da qualidade misc Qualidade dos cuidados de saúde misc Public aspects of medicine
topic_unstemmed	misc RA1-1270 misc Análise discriminante misc Satisfação dos consumidores misc Satisfação do paciente misc Gestão de qualidade total misc Garantia de qualidade dos cuidados de saúde misc Controle da qualidade misc Qualidade dos cuidados de saúde misc Public aspects of medicine
topic_browse	misc RA1-1270 misc Análise discriminante misc Satisfação dos consumidores misc Satisfação do paciente misc Gestão de qualidade total misc Garantia de qualidade dos cuidados de saúde misc Controle da qualidade misc Qualidade dos cuidados de saúde misc Public aspects of medicine
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title_sort	role of discriminant analysis in the refinement of customer satisfaction assessment
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title_auth	The role of discriminant analysis in the refinement of customer satisfaction assessment
abstract	OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one.
abstractGer	OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one.
abstract_unstemmed	OBJECTIVE: To test discriminant analysis as a method of turning the information of a routine customer satisfaction survey (CSS) into a more accurate decision-making tool. METHODS: A 7-question, 10-multiple choice, self-applied questionnaire was used to study a sample of patients seen in two outpatient care units in Valparaíso, Chile, one of primary care (n=100) and the other of secondary care (n=249). Two cutting points were considered in the dependent variable (final satisfaction score): satisfied versus unsatisfied, and very satisfied versus all others. Results were compared with empirical measures (proportion of satisfied individuals, proportion of unsatisfied individuals and size of the median). RESULTS: The response rate was very high, over 97.0% in both units. A new variable, medical attention, was revealed, as explaining satisfaction at the primary care unit. The proportion of the total variability explained by the model was very high (over 99.4%) in both units, when comparing satisfied with unsatisfied customers. In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). It measured the contribution of each independent variable to the explanation of the variation of the dependent one.
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title_short	The role of discriminant analysis in the refinement of customer satisfaction assessment
url	https://doi.org/10.1590/s0034-89102000000600010 https://doaj.org/article/bfc221a27fef42e693f401bc72c9fa72 http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102000000600010&lng=en&tlng=en https://doaj.org/toc/1518-8787
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In the analysis of very satisfied versus all other customers, significant relationship was identified only in the case of the primary care unit, which explained a small proportion of the variability (41.9%). CONCLUSIONS: Discriminant analysis identified relationships not revealed by the previous analysis. It provided information about the proportion of the variability explained by the model. It identified non-significant relationships suggested by empirical analysis (e.g. the case of the relation very satisfied versus others in the secondary care unit). 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The role of discriminant analysis in the refinement of customer satisfaction assessment

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