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This paper aims to quantify the quality of peer reviews, evaluate them from different perspectives and develop a model to predict the review quality. In addition, this paper investigates effective features to distinguish the reviews' quality. 

First, a fine-grained data set including peer review data, citations and review conformity scores was constructed. Second, metrics were proposed to evaluate the quality of peer reviews from three aspects. Third, five categories of features were proposed in terms of reviews, submissions and responses using natural language processing (NLP) techniques. Finally, different machine learning models were applied to predict the review quality, and feature analysis was performed to understand effective features.

The analysis results revealed that reviewers become more conservative and the review quality becomes worse over time in terms of these indicators. Among the three models, random forest model achieves the best performance on all three tasks. Sentiment polarity, review length, response length and readability are important factors that distinguish peer reviews’ quality, which can help meta-reviewers value more worthy reviews when making final decisions.

This study provides a new perspective for assessing review quality. Another originality of the research lies in the proposal of a novelty task that predict review quality. To address this task, a novel model was proposed which incorporated various of feature sets, thereby deepening the understanding of peer reviews.

This paper aims to draw upon extant theory and research to delineate the fundamental factors that impact how women evaluate disparaging humor directed at them. The conceptual framework presented outlines the most fundamental organizational-, interpersonal- and individual-level factors that influence the accuracy of such evaluation.

This is a conceptual paper that offers both a review of extant humor and gender research and theory and the presentation of a theoretical model that classifies sources of influence on evaluations of sexist humor from the perspective of the target.

Organization-, interpersonal- and individual-level factors are identified as sources of influence on women’s perception and evaluation of sexist humor leveled at them. This classification identifies factors including organizational power dynamics, egalitarian norms, interpersonal trust, target self-esteem and feminist identity.

This paper offers a conceptual framework to guide future studies in more systematically examining the sources of influence on female targets’ capacity to recognize when they are the “punchline” of sexist humor.

The conceptual model developed in this paper offers important implications for managers and leaders in organizations in assisting targets to recognize instances of sexist humor directed at them. The aim is to arm potential victims with the knowledge necessary to foster awareness of their treatment in the workplace and to improve the accuracy of evaluation of workplace attitudes that may often nurture a sense of approval or apathy regarding displays of sexist humor.

This paper presents a novel classification of sources of influence on female targets’ evaluation of sexist humor in the workplace.

The purpose of this paper is twofold. Firstly, the paper aims to determine the separate effects of the COVID-19 pandemic and government actions represented by the index of stringency, containment and economic support on the attractiveness of foreign direct investment (FDI). Secondly, the paper aims to explore the impact of the interactions between the COVID-19 epidemic and government interventions on FDI.

The study uses a panel data set of 30 Asian countries during the two pandemic years 2020 and 2021 to investigate the effect of government actions on the resilience of FDI attractiveness factors.

The empirical results reveal the negative effect of COVID-19 on FDI inflows and attractiveness factors. However, government responses have a positive and statistically significant effect on the FDI attractiveness factors such as economic growth, trade openness and human and technological capital development and contribute to the economic recovery of the Asian region.

The empirical findings can provide useful information for policymakers in designing macroeconomic policies and taking government measures to improve their investment environment and attract FDI.

The study shows that government responses, economic support, containment and health policies are effective in containing viruses, reducing the impact of the COVID-19 pandemic and strengthening resilience in FDI attractiveness factors. It also indicates that foreign investors are responding positively to government measures.

This study examines the determinants of medical crowdfunding performance. Drawing on signaling theory, the authors investigate how funding-related signals (funding goal and duration), story-related signals (text length, text sentiment, and use of first-person pronouns), and donor-related signals (donor identity disclosure) affect medical crowdfunding performance.

This study analyzed the data of 754 medical crowdfunding projects collected from the Qingsongchou platform in China to test the proposed model.

The empirical findings reveal that both funding goal and funding duration exhibit a U-shaped relationship with crowdfunding performance. Additionally, the authors find evidence that story text length and donor identity disclosure are positively related to crowdfunding performance, whereas the use of first-person pronouns is negatively related to crowdfunding performance.

This study extends the understanding of the determinants of medical crowdfunding performance through the signaling theory. Specifically, this study provides new insights into the roles of funding goal and funding duration in predicting medical crowdfunding performance and identifies several new predictors of crowdfunding performance, including the use of first-person pronouns in project story text and donor identity disclosure.

The COVID-19 pandemic has disrupted numerous businesses and upended the lives and shopping habits of most consumers. This study aims to examine the price sensitivity and the efficacy of online reviews during a pandemic crisis.

This study borrowed from the regulatory focus theory and heuristic-systematic model and used a unique longitudinal sample of 320,000 product/day observations from the jeans category, collected before and during the pandemic, to investigate how consumers’ online shopping behavior changed during the pandemic.

The results of several hierarchical linear modeling analyses revealed that during the pandemic consumers were less price-sensitive and more willing to pay price premiums for jeans. Furthermore, consumers were more (less) likely to be influenced by online review volume than valence. Finally, the results of a post-hoc study highlighted the potential role of regulatory focus as the underlying psychological mechanism explaining the effect of the pandemic.

This research contributes to the digital marketing and regulatory-focus literatures by showing that the COVID-19 pandemic may have triggered a prevention-focus state of mind and prompted consumers to place a greater value on online review volume than valence when shopping online (for jeans). Furthermore, this paper contributes to the pricing literature by offering further evidence that the pandemic may have inclined consumers to be less price-sensitive.