Purpose: The perception of an inferior learning experience is the main challenge for online learning, which leads to higher dropout rates in online courses. The purpose of this paper focuses on investigating how the multi-dimensional construct of social presence would affect the behavior of online learners.Design/methodology/approach: A conceptual model that describes online learner behaviors is proposed by including the four social presence variables, learning satisfaction and continuance intention, which is examined via the data collected by a survey of 237 online learners from a typical online learning platform in China. The relationships between variables were tested via structural equation modeling.Findings: The results revealed that the intimate and immersive social factors have positive impacts on learning satisfaction, which in turn results in continuous intention in online learning. Thus, online learning platform providers should seriously consider building an intimate and immersive online environment for learners. Furthermore, this research provides a more comprehensive understanding of online learning from a social presence perspective for researchers and practitioners.Originality/value: The study contributes to a better understanding of the social presence which is conceptualized as a four-dimensional construct, and shows how social factors influence learning satisfaction and continuous intention, providing a deeper understanding of the core relationship between social aspects and learning performance in online learning.

It is becoming an important innovation strategy for firms to gather the user-idea extensively through open innovation communities (OICs). However, screening out valuable ideas from massive user ideas in an OIC is a huge challenge for the firm. It is very important to identify the relevant factors that influence user-idea selection. Drawing upon persuasion theory, we develop a conceptual model integrating idea quality characteristics, idea contributor characteristics, and idea emotion characteristics to explain the likelihood of idea selection, using 23,165 user ideas in the MIUI Community hosted by Xiaomi, a Chinese mobile phone manufacturer ranked among the Fortune Global 500. The empirical results show that these characteristics variables have significant impacts on user-idea selection. Specifically, the length of the idea and title has an inverted U-shaped relationship with idea selection. The emotions contained in user ideas have a significant positive impact on idea selection, and user attention negatively moderates the relationship between emotion and idea selection. This study contributes to the user co-creation literature by offering a persuasion perspective to explain user-idea selection in OICs. It also offers novel insights for building reasonable rules in OICs to guide user behavior for managers.

Purpose: 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.Design/methodology/approach: 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.Findings: 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.Originality/value: 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.