Is information normalization helpful in online communication? Evidence from online healthcare consultation
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| Vydáno v: | Internet Research vol. 35, no. 2 (2025), p. 719-749 |
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Emerald Group Publishing Limited
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| 001 | 3177795785 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1066-2243 | ||
| 022 | |a 2054-5657 | ||
| 022 | |a 1051-4805 | ||
| 024 | 7 | |a 10.1108/INTR-05-2023-0348 |2 doi | |
| 035 | |a 3177795785 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 46159 |2 nlm | ||
| 100 | 1 | |a Wang, Xuan |u School of Management, Shanghai University of International Business and Economics, Shanghai, China | |
| 245 | 1 | |a Is information normalization helpful in online communication? Evidence from online healthcare consultation | |
| 260 | |b Emerald Group Publishing Limited |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a PurposeThis study aims to investigate the role of information normalization in online healthcare consultation, a typical complex human-to-human communication requiring both effectiveness and efficiency. The globalization and digitization trend calls for high-quality information, and normalization is considered an effective method for improving information quality. Meanwhile, some researchers argued that excessive normalization (standardized answers) may be perceived as impersonal, repetitive, and cold. Thus, it is not appreciated for human-to-human communication, for instance, when patients are anxious about their health condition (e.g. with high-risk disease) in online healthcare consultation. Therefore, the role of information normalization in human communication is worthy to be explored.Design/methodology/approachData were collected from one of the largest online healthcare consultation platforms (Dxy.com). This study expanded the existing information quality model by introducing information normalization as a new dimension. Information normalization was assessed using medical templates, extracted through natural language processing methods such as Bidirectional Encoder Representations from Transformers (BERT) and Latent Dirichlet Allocation (LDA). Patient decision-making behaviors, namely, consultant selection and satisfaction, were chosen to evaluate communication performance.FindingsThe results confirmed the positive impact of information normalization on communication performance. Additionally, a negative moderating effect of disease risk on the relationship between information normalization and patient decision-making was identified. Furthermore, the study demonstrated that information normalization can be enhanced through experiential learning.Originality/valueThese findings highlighted the significance of information normalization in online healthcare communication and extended the existing information quality model. It also facilitated patient decision-making on online healthcare platforms by providing a comprehensive information quality measurement. In addition, the moderating effects indicated the contradiction between informational support and emotional support, enriching the social support theory. | |
| 653 | |a Performance evaluation | ||
| 653 | |a Communication | ||
| 653 | |a User satisfaction | ||
| 653 | |a Human communication | ||
| 653 | |a Platforms | ||
| 653 | |a Decision making | ||
| 653 | |a Globalization | ||
| 653 | |a Patient satisfaction | ||
| 653 | |a Physicians | ||
| 653 | |a Quality assessment | ||
| 653 | |a Health care | ||
| 653 | |a Effectiveness | ||
| 653 | |a Information processing | ||
| 653 | |a Quality of service | ||
| 653 | |a Ratings & rankings | ||
| 653 | |a Natural language processing | ||
| 653 | |a Emotional support | ||
| 653 | |a Efficiency | ||
| 653 | |a Bidirectionality | ||
| 653 | |a Measurement | ||
| 653 | |a Humans | ||
| 653 | |a Experiential learning | ||
| 653 | |a Support theory | ||
| 653 | |a High risk | ||
| 653 | |a Patients | ||
| 653 | |a Social support | ||
| 653 | |a Information | ||
| 653 | |a Computer mediated communication | ||
| 653 | |a Internet | ||
| 653 | |a Health services | ||
| 653 | |a Disease | ||
| 653 | |a Digitization | ||
| 653 | |a Satisfaction | ||
| 653 | |a Normalization | ||
| 653 | |a Rating Scales | ||
| 653 | |a Primary Health Care | ||
| 653 | |a Influence of Technology | ||
| 653 | |a Program Evaluation | ||
| 653 | |a Medical Services | ||
| 653 | |a Knowledge Level | ||
| 653 | |a Communication Strategies | ||
| 653 | |a Language Processing | ||
| 653 | |a Medical Care Evaluation | ||
| 700 | 1 | |a Huang, Tao |u Guanghua School of Management, Peking University, Beijing, China | |
| 700 | 1 | |a Zhang, Wenping |u School of Information, Renmin University of China, Beijing, China | |
| 700 | 1 | |a Zeng, Qingfeng |u Department of Digital Economics, Shanghai University of Finance and Economics, Shanghai, China | |
| 700 | 1 | |a Sun, Xin |u Shanghai Jiao Tong University, Shanghai, China | |
| 773 | 0 | |t Internet Research |g vol. 35, no. 2 (2025), p. 719-749 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3177795785/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3177795785/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3177795785/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |