A Model for Observation, Structural, and Household Heterogeneity in Panel Data
Abstract Standard methods of understanding customer behavior in marketing allow for differences in sensitivity across consumers, but often assume that the sensitivity of a particular individual is fixed through time. In many situations, this assumption may not be valid. Both the importance of variab...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yang, Sha [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2000 |
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| Schlagwörter: |
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| Anmerkung: |
© Kluwer Academic Publishers 2000 |
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| Übergeordnetes Werk: |
Enthalten in: Marketing letters - Kluwer Academic Publishers, 1989, 11(2000), 2 vom: Mai, Seite 137-149 |
|---|---|
| Übergeordnetes Werk: |
volume:11 ; year:2000 ; number:2 ; month:05 ; pages:137-149 |
| Links: |
|---|
| DOI / URN: |
10.1023/A:1008190707034 |
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OLC2070810100 |
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| 520 | |a Abstract Standard methods of understanding customer behavior in marketing allow for differences in sensitivity across consumers, but often assume that the sensitivity of a particular individual is fixed through time. In many situations, this assumption may not be valid. Both the importance of variables, and the manner that they are combined to form an overall measure of value for an offer, can change. In this paper we propose an approach of modeling a customer's purchase history that allows identification of when these aspects of customer behavior are likely to change. This information is useful, for example, in planning when particular customers will be most likely to respond to an offer. Our approach nests common methods of dealing with individual differences, and allows for the introduction of covariates associated with changes in customer behavior. We illustrate our model with data from a national sample of credit card usage and adoption. | ||
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10.1023/A:1008190707034 doi (DE-627)OLC2070810100 (DE-He213)A:1008190707034-p DE-627 ger DE-627 rakwb eng 380 VZ 3,2 ssgn 85.00 bkl Yang, Sha verfasserin aut A Model for Observation, Structural, and Household Heterogeneity in Panel Data 2000 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 2000 Abstract Standard methods of understanding customer behavior in marketing allow for differences in sensitivity across consumers, but often assume that the sensitivity of a particular individual is fixed through time. In many situations, this assumption may not be valid. Both the importance of variables, and the manner that they are combined to form an overall measure of value for an offer, can change. In this paper we propose an approach of modeling a customer's purchase history that allows identification of when these aspects of customer behavior are likely to change. This information is useful, for example, in planning when particular customers will be most likely to respond to an offer. Our approach nests common methods of dealing with individual differences, and allows for the introduction of covariates associated with changes in customer behavior. We illustrate our model with data from a national sample of credit card usage and adoption. Marketing Standard Method Individual Difference Common Method Panel Data Allenby, Greg M. aut Enthalten in Marketing letters Kluwer Academic Publishers, 1989 11(2000), 2 vom: Mai, Seite 137-149 (DE-627)170251217 (DE-600)1031012-5 (DE-576)023106794 0923-0645 nnns volume:11 year:2000 number:2 month:05 pages:137-149 https://doi.org/10.1023/A:1008190707034 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW GBV_ILN_31 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4125 GBV_ILN_4311 GBV_ILN_4318 85.00 VZ AR 11 2000 2 05 137-149 |
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10.1023/A:1008190707034 doi (DE-627)OLC2070810100 (DE-He213)A:1008190707034-p DE-627 ger DE-627 rakwb eng 380 VZ 3,2 ssgn 85.00 bkl Yang, Sha verfasserin aut A Model for Observation, Structural, and Household Heterogeneity in Panel Data 2000 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 2000 Abstract Standard methods of understanding customer behavior in marketing allow for differences in sensitivity across consumers, but often assume that the sensitivity of a particular individual is fixed through time. In many situations, this assumption may not be valid. Both the importance of variables, and the manner that they are combined to form an overall measure of value for an offer, can change. In this paper we propose an approach of modeling a customer's purchase history that allows identification of when these aspects of customer behavior are likely to change. This information is useful, for example, in planning when particular customers will be most likely to respond to an offer. Our approach nests common methods of dealing with individual differences, and allows for the introduction of covariates associated with changes in customer behavior. We illustrate our model with data from a national sample of credit card usage and adoption. Marketing Standard Method Individual Difference Common Method Panel Data Allenby, Greg M. aut Enthalten in Marketing letters Kluwer Academic Publishers, 1989 11(2000), 2 vom: Mai, Seite 137-149 (DE-627)170251217 (DE-600)1031012-5 (DE-576)023106794 0923-0645 nnns volume:11 year:2000 number:2 month:05 pages:137-149 https://doi.org/10.1023/A:1008190707034 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW GBV_ILN_31 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4125 GBV_ILN_4311 GBV_ILN_4318 85.00 VZ AR 11 2000 2 05 137-149 |
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10.1023/A:1008190707034 doi (DE-627)OLC2070810100 (DE-He213)A:1008190707034-p DE-627 ger DE-627 rakwb eng 380 VZ 3,2 ssgn 85.00 bkl Yang, Sha verfasserin aut A Model for Observation, Structural, and Household Heterogeneity in Panel Data 2000 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 2000 Abstract Standard methods of understanding customer behavior in marketing allow for differences in sensitivity across consumers, but often assume that the sensitivity of a particular individual is fixed through time. In many situations, this assumption may not be valid. Both the importance of variables, and the manner that they are combined to form an overall measure of value for an offer, can change. In this paper we propose an approach of modeling a customer's purchase history that allows identification of when these aspects of customer behavior are likely to change. This information is useful, for example, in planning when particular customers will be most likely to respond to an offer. Our approach nests common methods of dealing with individual differences, and allows for the introduction of covariates associated with changes in customer behavior. We illustrate our model with data from a national sample of credit card usage and adoption. Marketing Standard Method Individual Difference Common Method Panel Data Allenby, Greg M. aut Enthalten in Marketing letters Kluwer Academic Publishers, 1989 11(2000), 2 vom: Mai, Seite 137-149 (DE-627)170251217 (DE-600)1031012-5 (DE-576)023106794 0923-0645 nnns volume:11 year:2000 number:2 month:05 pages:137-149 https://doi.org/10.1023/A:1008190707034 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW GBV_ILN_31 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4125 GBV_ILN_4311 GBV_ILN_4318 85.00 VZ AR 11 2000 2 05 137-149 |
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10.1023/A:1008190707034 doi (DE-627)OLC2070810100 (DE-He213)A:1008190707034-p DE-627 ger DE-627 rakwb eng 380 VZ 3,2 ssgn 85.00 bkl Yang, Sha verfasserin aut A Model for Observation, Structural, and Household Heterogeneity in Panel Data 2000 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Kluwer Academic Publishers 2000 Abstract Standard methods of understanding customer behavior in marketing allow for differences in sensitivity across consumers, but often assume that the sensitivity of a particular individual is fixed through time. In many situations, this assumption may not be valid. Both the importance of variables, and the manner that they are combined to form an overall measure of value for an offer, can change. In this paper we propose an approach of modeling a customer's purchase history that allows identification of when these aspects of customer behavior are likely to change. This information is useful, for example, in planning when particular customers will be most likely to respond to an offer. Our approach nests common methods of dealing with individual differences, and allows for the introduction of covariates associated with changes in customer behavior. We illustrate our model with data from a national sample of credit card usage and adoption. Marketing Standard Method Individual Difference Common Method Panel Data Allenby, Greg M. aut Enthalten in Marketing letters Kluwer Academic Publishers, 1989 11(2000), 2 vom: Mai, Seite 137-149 (DE-627)170251217 (DE-600)1031012-5 (DE-576)023106794 0923-0645 nnns volume:11 year:2000 number:2 month:05 pages:137-149 https://doi.org/10.1023/A:1008190707034 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-WIW GBV_ILN_31 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4082 GBV_ILN_4125 GBV_ILN_4311 GBV_ILN_4318 85.00 VZ AR 11 2000 2 05 137-149 |
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Abstract Standard methods of understanding customer behavior in marketing allow for differences in sensitivity across consumers, but often assume that the sensitivity of a particular individual is fixed through time. In many situations, this assumption may not be valid. Both the importance of variables, and the manner that they are combined to form an overall measure of value for an offer, can change. In this paper we propose an approach of modeling a customer's purchase history that allows identification of when these aspects of customer behavior are likely to change. This information is useful, for example, in planning when particular customers will be most likely to respond to an offer. Our approach nests common methods of dealing with individual differences, and allows for the introduction of covariates associated with changes in customer behavior. We illustrate our model with data from a national sample of credit card usage and adoption. © Kluwer Academic Publishers 2000 |
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Abstract Standard methods of understanding customer behavior in marketing allow for differences in sensitivity across consumers, but often assume that the sensitivity of a particular individual is fixed through time. In many situations, this assumption may not be valid. Both the importance of variables, and the manner that they are combined to form an overall measure of value for an offer, can change. In this paper we propose an approach of modeling a customer's purchase history that allows identification of when these aspects of customer behavior are likely to change. This information is useful, for example, in planning when particular customers will be most likely to respond to an offer. Our approach nests common methods of dealing with individual differences, and allows for the introduction of covariates associated with changes in customer behavior. We illustrate our model with data from a national sample of credit card usage and adoption. © Kluwer Academic Publishers 2000 |
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Abstract Standard methods of understanding customer behavior in marketing allow for differences in sensitivity across consumers, but often assume that the sensitivity of a particular individual is fixed through time. In many situations, this assumption may not be valid. Both the importance of variables, and the manner that they are combined to form an overall measure of value for an offer, can change. In this paper we propose an approach of modeling a customer's purchase history that allows identification of when these aspects of customer behavior are likely to change. This information is useful, for example, in planning when particular customers will be most likely to respond to an offer. Our approach nests common methods of dealing with individual differences, and allows for the introduction of covariates associated with changes in customer behavior. We illustrate our model with data from a national sample of credit card usage and adoption. © Kluwer Academic Publishers 2000 |
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2024-07-04T02:19:27.128Z |
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