The influence of patient-generated reviews and doctor-patient relationship on online consultations in China
Gespeichert in:
| Autor*in: |
Hu, Yajie [verfasserIn] Zhou, Huiwen [verfasserIn] Chen, Yuangao [verfasserIn] Yao, Jianrong [verfasserIn] Su, Jiangwu [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Electronic commerce research - Dordrecht : Springer Science Business Media B.V., 2001, 23(2023), 2 vom: Juni, Seite 1115-1141 |
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| Übergeordnetes Werk: |
volume:23 ; year:2023 ; number:2 ; month:06 ; pages:1115-1141 |
| Links: |
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| DOI / URN: |
10.1007/s10660-021-09506-8 |
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| Katalog-ID: |
1844764931 |
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| 982 | |2 26 |1 00 |x DE-206 |b Online reviews are increasingly being used and researched by people worldwide. Compared with previous studies on traditional products or services, research focused on online health communities (OHCs) is still insufficient. Thus, based on cue diagnosticity theory, this research concentrates on combining two mainstream studies by incorporating the patient-generated review with the unique characteristics of online medical services–the doctor-patient relationship–to study the information processing issues in choosing consultations. We clawed the dataset, including 2865 doctors related to 152,864 patient-generated reviews and information, from the GoodDoctor website. We then employed a negative binomial regression to test our hypotheses. Interestingly, we found that the effects of review length and review volume on doctors’ consultations can be negatively moderated by the doctor-patient relationship. Our findings can serve patients, doctors, platform managers, and others to optimize the application of patients’ information processing when choosing consultations. | ||
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10.1007/s10660-021-09506-8 doi (DE-627)1844764931 (DE-599)KXP1844764931 DE-627 ger DE-627 rda eng Hu, Yajie verfasserin (DE-588)1292283416 (DE-627)1847694306 aut The influence of patient-generated reviews and doctor-patient relationship on online consultations in China Yajie Hu, Huiwen Zhou, Yuangao Chen, Jianrong Yao, Jiangwu Su 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cue diagnosticity theory (dpeaa)DE-206 Doctor-patient relationship (dpeaa)DE-206 Online health communities (dpeaa)DE-206 Patient-generated review (dpeaa)DE-206 Zhou, Huiwen verfasserin (DE-588)1292283467 (DE-627)1847694454 aut Chen, Yuangao verfasserin (DE-588)1023184079 (DE-627)717305910 (DE-576)366494228 aut Yao, Jianrong verfasserin (DE-588)1023184095 (DE-627)717305988 (DE-576)366494201 aut Su, Jiangwu verfasserin (DE-588)1292283645 (DE-627)1847694713 aut Enthalten in Electronic commerce research Dordrecht : Springer Science Business Media B.V., 2001 23(2023), 2 vom: Juni, Seite 1115-1141 Online-Ressource (DE-627)325615047 (DE-600)2038488-9 (DE-576)121192482 1572-9362 nnns volume:23 year:2023 number:2 month:06 pages:1115-1141 https://doi.org/10.1007/s10660-021-09506-8 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2023 2 6 1115-1141 26 01 0206 4319138740 x1z 08-05-23 26 00 DE-206 Online reviews are increasingly being used and researched by people worldwide. Compared with previous studies on traditional products or services, research focused on online health communities (OHCs) is still insufficient. Thus, based on cue diagnosticity theory, this research concentrates on combining two mainstream studies by incorporating the patient-generated review with the unique characteristics of online medical services–the doctor-patient relationship–to study the information processing issues in choosing consultations. We clawed the dataset, including 2865 doctors related to 152,864 patient-generated reviews and information, from the GoodDoctor website. We then employed a negative binomial regression to test our hypotheses. Interestingly, we found that the effects of review length and review volume on doctors’ consultations can be negatively moderated by the doctor-patient relationship. Our findings can serve patients, doctors, platform managers, and others to optimize the application of patients’ information processing when choosing consultations. |
| spelling |
10.1007/s10660-021-09506-8 doi (DE-627)1844764931 (DE-599)KXP1844764931 DE-627 ger DE-627 rda eng Hu, Yajie verfasserin (DE-588)1292283416 (DE-627)1847694306 aut The influence of patient-generated reviews and doctor-patient relationship on online consultations in China Yajie Hu, Huiwen Zhou, Yuangao Chen, Jianrong Yao, Jiangwu Su 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cue diagnosticity theory (dpeaa)DE-206 Doctor-patient relationship (dpeaa)DE-206 Online health communities (dpeaa)DE-206 Patient-generated review (dpeaa)DE-206 Zhou, Huiwen verfasserin (DE-588)1292283467 (DE-627)1847694454 aut Chen, Yuangao verfasserin (DE-588)1023184079 (DE-627)717305910 (DE-576)366494228 aut Yao, Jianrong verfasserin (DE-588)1023184095 (DE-627)717305988 (DE-576)366494201 aut Su, Jiangwu verfasserin (DE-588)1292283645 (DE-627)1847694713 aut Enthalten in Electronic commerce research Dordrecht : Springer Science Business Media B.V., 2001 23(2023), 2 vom: Juni, Seite 1115-1141 Online-Ressource (DE-627)325615047 (DE-600)2038488-9 (DE-576)121192482 1572-9362 nnns volume:23 year:2023 number:2 month:06 pages:1115-1141 https://doi.org/10.1007/s10660-021-09506-8 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2023 2 6 1115-1141 26 01 0206 4319138740 x1z 08-05-23 26 00 DE-206 Online reviews are increasingly being used and researched by people worldwide. Compared with previous studies on traditional products or services, research focused on online health communities (OHCs) is still insufficient. Thus, based on cue diagnosticity theory, this research concentrates on combining two mainstream studies by incorporating the patient-generated review with the unique characteristics of online medical services–the doctor-patient relationship–to study the information processing issues in choosing consultations. We clawed the dataset, including 2865 doctors related to 152,864 patient-generated reviews and information, from the GoodDoctor website. We then employed a negative binomial regression to test our hypotheses. Interestingly, we found that the effects of review length and review volume on doctors’ consultations can be negatively moderated by the doctor-patient relationship. Our findings can serve patients, doctors, platform managers, and others to optimize the application of patients’ information processing when choosing consultations. |
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10.1007/s10660-021-09506-8 doi (DE-627)1844764931 (DE-599)KXP1844764931 DE-627 ger DE-627 rda eng Hu, Yajie verfasserin (DE-588)1292283416 (DE-627)1847694306 aut The influence of patient-generated reviews and doctor-patient relationship on online consultations in China Yajie Hu, Huiwen Zhou, Yuangao Chen, Jianrong Yao, Jiangwu Su 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cue diagnosticity theory (dpeaa)DE-206 Doctor-patient relationship (dpeaa)DE-206 Online health communities (dpeaa)DE-206 Patient-generated review (dpeaa)DE-206 Zhou, Huiwen verfasserin (DE-588)1292283467 (DE-627)1847694454 aut Chen, Yuangao verfasserin (DE-588)1023184079 (DE-627)717305910 (DE-576)366494228 aut Yao, Jianrong verfasserin (DE-588)1023184095 (DE-627)717305988 (DE-576)366494201 aut Su, Jiangwu verfasserin (DE-588)1292283645 (DE-627)1847694713 aut Enthalten in Electronic commerce research Dordrecht : Springer Science Business Media B.V., 2001 23(2023), 2 vom: Juni, Seite 1115-1141 Online-Ressource (DE-627)325615047 (DE-600)2038488-9 (DE-576)121192482 1572-9362 nnns volume:23 year:2023 number:2 month:06 pages:1115-1141 https://doi.org/10.1007/s10660-021-09506-8 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2023 2 6 1115-1141 26 01 0206 4319138740 x1z 08-05-23 26 00 DE-206 Online reviews are increasingly being used and researched by people worldwide. Compared with previous studies on traditional products or services, research focused on online health communities (OHCs) is still insufficient. Thus, based on cue diagnosticity theory, this research concentrates on combining two mainstream studies by incorporating the patient-generated review with the unique characteristics of online medical services–the doctor-patient relationship–to study the information processing issues in choosing consultations. We clawed the dataset, including 2865 doctors related to 152,864 patient-generated reviews and information, from the GoodDoctor website. We then employed a negative binomial regression to test our hypotheses. Interestingly, we found that the effects of review length and review volume on doctors’ consultations can be negatively moderated by the doctor-patient relationship. Our findings can serve patients, doctors, platform managers, and others to optimize the application of patients’ information processing when choosing consultations. |
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10.1007/s10660-021-09506-8 doi (DE-627)1844764931 (DE-599)KXP1844764931 DE-627 ger DE-627 rda eng Hu, Yajie verfasserin (DE-588)1292283416 (DE-627)1847694306 aut The influence of patient-generated reviews and doctor-patient relationship on online consultations in China Yajie Hu, Huiwen Zhou, Yuangao Chen, Jianrong Yao, Jiangwu Su 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cue diagnosticity theory (dpeaa)DE-206 Doctor-patient relationship (dpeaa)DE-206 Online health communities (dpeaa)DE-206 Patient-generated review (dpeaa)DE-206 Zhou, Huiwen verfasserin (DE-588)1292283467 (DE-627)1847694454 aut Chen, Yuangao verfasserin (DE-588)1023184079 (DE-627)717305910 (DE-576)366494228 aut Yao, Jianrong verfasserin (DE-588)1023184095 (DE-627)717305988 (DE-576)366494201 aut Su, Jiangwu verfasserin (DE-588)1292283645 (DE-627)1847694713 aut Enthalten in Electronic commerce research Dordrecht : Springer Science Business Media B.V., 2001 23(2023), 2 vom: Juni, Seite 1115-1141 Online-Ressource (DE-627)325615047 (DE-600)2038488-9 (DE-576)121192482 1572-9362 nnns volume:23 year:2023 number:2 month:06 pages:1115-1141 https://doi.org/10.1007/s10660-021-09506-8 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2023 2 6 1115-1141 26 01 0206 4319138740 x1z 08-05-23 26 00 DE-206 Online reviews are increasingly being used and researched by people worldwide. Compared with previous studies on traditional products or services, research focused on online health communities (OHCs) is still insufficient. Thus, based on cue diagnosticity theory, this research concentrates on combining two mainstream studies by incorporating the patient-generated review with the unique characteristics of online medical services–the doctor-patient relationship–to study the information processing issues in choosing consultations. We clawed the dataset, including 2865 doctors related to 152,864 patient-generated reviews and information, from the GoodDoctor website. We then employed a negative binomial regression to test our hypotheses. Interestingly, we found that the effects of review length and review volume on doctors’ consultations can be negatively moderated by the doctor-patient relationship. Our findings can serve patients, doctors, platform managers, and others to optimize the application of patients’ information processing when choosing consultations. |
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10.1007/s10660-021-09506-8 doi (DE-627)1844764931 (DE-599)KXP1844764931 DE-627 ger DE-627 rda eng Hu, Yajie verfasserin (DE-588)1292283416 (DE-627)1847694306 aut The influence of patient-generated reviews and doctor-patient relationship on online consultations in China Yajie Hu, Huiwen Zhou, Yuangao Chen, Jianrong Yao, Jiangwu Su 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Cue diagnosticity theory (dpeaa)DE-206 Doctor-patient relationship (dpeaa)DE-206 Online health communities (dpeaa)DE-206 Patient-generated review (dpeaa)DE-206 Zhou, Huiwen verfasserin (DE-588)1292283467 (DE-627)1847694454 aut Chen, Yuangao verfasserin (DE-588)1023184079 (DE-627)717305910 (DE-576)366494228 aut Yao, Jianrong verfasserin (DE-588)1023184095 (DE-627)717305988 (DE-576)366494201 aut Su, Jiangwu verfasserin (DE-588)1292283645 (DE-627)1847694713 aut Enthalten in Electronic commerce research Dordrecht : Springer Science Business Media B.V., 2001 23(2023), 2 vom: Juni, Seite 1115-1141 Online-Ressource (DE-627)325615047 (DE-600)2038488-9 (DE-576)121192482 1572-9362 nnns volume:23 year:2023 number:2 month:06 pages:1115-1141 https://doi.org/10.1007/s10660-021-09506-8 Resolving-System lizenzpflichtig GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 23 2023 2 6 1115-1141 26 01 0206 4319138740 x1z 08-05-23 26 00 DE-206 Online reviews are increasingly being used and researched by people worldwide. Compared with previous studies on traditional products or services, research focused on online health communities (OHCs) is still insufficient. Thus, based on cue diagnosticity theory, this research concentrates on combining two mainstream studies by incorporating the patient-generated review with the unique characteristics of online medical services–the doctor-patient relationship–to study the information processing issues in choosing consultations. We clawed the dataset, including 2865 doctors related to 152,864 patient-generated reviews and information, from the GoodDoctor website. We then employed a negative binomial regression to test our hypotheses. Interestingly, we found that the effects of review length and review volume on doctors’ consultations can be negatively moderated by the doctor-patient relationship. Our findings can serve patients, doctors, platform managers, and others to optimize the application of patients’ information processing when choosing consultations. |
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26 00 DE-206 Online reviews are increasingly being used and researched by people worldwide. Compared with previous studies on traditional products or services, research focused on online health communities (OHCs) is still insufficient. Thus, based on cue diagnosticity theory, this research concentrates on combining two mainstream studies by incorporating the patient-generated review with the unique characteristics of online medical services–the doctor-patient relationship–to study the information processing issues in choosing consultations. We clawed the dataset, including 2865 doctors related to 152,864 patient-generated reviews and information, from the GoodDoctor website. We then employed a negative binomial regression to test our hypotheses. Interestingly, we found that the effects of review length and review volume on doctors’ consultations can be negatively moderated by the doctor-patient relationship. Our findings can serve patients, doctors, platform managers, and others to optimize the application of patients’ information processing when choosing consultations The influence of patient-generated reviews and doctor-patient relationship on online consultations in China Yajie Hu, Huiwen Zhou, Yuangao Chen, Jianrong Yao, Jiangwu Su Cue diagnosticity theory (dpeaa)DE-206 Doctor-patient relationship (dpeaa)DE-206 Online health communities (dpeaa)DE-206 Patient-generated review (dpeaa)DE-206 |
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code="h">1115-1141</subfield></datafield><datafield tag="980" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">01</subfield><subfield code="x">0206</subfield><subfield code="b">4319138740</subfield><subfield code="y">x1z</subfield><subfield code="z">08-05-23</subfield></datafield><datafield tag="982" ind1=" " ind2=" "><subfield code="2">26</subfield><subfield code="1">00</subfield><subfield code="x">DE-206</subfield><subfield code="b">Online reviews are increasingly being used and researched by people worldwide. Compared with previous studies on traditional products or services, research focused on online health communities (OHCs) is still insufficient. Thus, based on cue diagnosticity theory, this research concentrates on combining two mainstream studies by incorporating the patient-generated review with the unique characteristics of online medical services–the doctor-patient relationship–to study the information processing issues in choosing consultations. We clawed the dataset, including 2865 doctors related to 152,864 patient-generated reviews and information, from the GoodDoctor website. We then employed a negative binomial regression to test our hypotheses. Interestingly, we found that the effects of review length and review volume on doctors’ consultations can be negatively moderated by the doctor-patient relationship. Our findings can serve patients, doctors, platform managers, and others to optimize the application of patients’ information processing when choosing consultations.</subfield></datafield></record></collection>
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| score |
7.400613 |