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While corporate social responsibility (CSR) has been gaining support for the role it plays in employee outcomes, such as organizational identification (OID), the view of CSR from a social identity perspective is underdeveloped. This conceptual chapter explores the role of social identity processes grounded in organizational justice to develop a model of CSR attributions and the moderating role these attributions play in organizational member outcomes. CSR is understood as the relational processes happening with stakeholders, and these relationships engage specific organizational identity orientations. The social identity process flows from there, resulting in CSR attributions including strategic, relational, and virtuous. Using social identity, organizational identity, and organizational justice, this chapter makes two specific contributions: a CSR attribution typology grounded in organizational justice and the moderating impact of these attributions between activated justice dimensions and resulting organizational member outcomes.

This 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.

Data 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.

The 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.

These 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.