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PurposeThis paper aims to study whether the adoption of an entry mode that fits the social trust level contributes to the improvement of foreign subsidiary performance.Design/methodology/approachThe authors used the Probit model, linear regression, strategic fit approach and instrumental variable regression. The sample was made up of 11,095 observations of Chinese multinational enterprises' foreign subsidiaries in 54 countries from 2005 to 2020.FindingsThe results suggest that a host country with a high level of social trust results in fewer difficulties for enterprises in gaining legitimacy, thus foreign subsidiaries are more likely to select the wholly owned entry mode. The results also show that the effect is contingent on the formal institutions of host countries. The results of the mechanism test suggest that social trust influences subsidiaries' entry mode choice by reducing information asymmetry, costs and uncertainty risks. This study further finds that selecting a fit entry mode based on social trust level substantially increases foreign subsidiary performance and this effect is more significant when multinational enterprises (MNEs) are state-owned enterprises (SOEs).Research limitations/implicationsThe main limitation of this paper is its only focus on foreign subsidiaries of Chinese MNEs, which may limit the generalizability of research findings.Originality/valueThis paper responds to the call for conducting more research on informal institutions. Findings highlight the critical role of informal institutions in helping foreign subsidiaries in gaining legitimacy in host countries and the essentialness of selecting a fit entry mode based on the informal institutions of host countries for the development of foreign subsidiaries.

PurposeOnline reviews are regarded as a source of information for decision-making because of the abundance and ready availability of information. Whereas, the sheer volume of online reviews makes it hard for consumers, especially the older adults who perceive more difficulties in reading reviews and obtaining information compared to younger adults, to locate the useful ones. The main objective of this study is to propose an effective method to locate valuable reviews of mobile phones for older adults. Besides, the authors also want to explore what characteristics of the technology older adults prefer. This will benefit both e-retailers and e-commerce platforms.Design/methodology/approachAfter collecting online reviews related to mobile phones designed for older adults from a popular Chinese e-commerce platform (JD Mall), topic modeling, term frequency-inverse document frequency (TF-IDF), and linguistic inquiry and word count (LIWC) methods were applied to extract latent topics and uncover potential dimensions that consumers frequently referred to in their reviews. According to consumers' attitudes towards different popular topics, seven machine learning models were employed to predict the usefulness and popularity of online reviews due to their excellent performance in prediction. To improve the performance, a weighted model based on the two best-performing models was built and evaluated.FindingsBased on the TF-IDF, topic modeling, and LIWC methods, the authors find that older adults are more interested in the exterior, sound, and communication functions of mobile phones. Besides, the weighted model (Random Forest: Decision Tree = 2:1) is the best model for predicting the online review popularity, while random forest performs best in predicting the perceived usefulness of online reviews.Practical implicationsThis study's findings can help e-commerce platforms and merchants identify the needs of the targeted consumers, predict reviews that will get more attention, and provide some early responses to some questions.Originality/valueThe results propose that older adults pay more attention to the mobile phones' exterior, sound, and communication function, guiding future research. Besides, this paper also enriches the current studies related to making predictions based on the information contained in the online reviews.

Chinese activist Liu Xiaobo (1955-2017)-awarded the Nobel Peace Prize while serving an eleven-year prison sentence-helped shatter longstanding barriers to freedom of organization and expression in China. This biography, written by one of his closest friends, retraces Liu Xiaobo's inspiring life, from his childhood years through his imprisonment. He became terminally ill while incarcerated and died July 13, 2017.