Examining the characteristics and effectiveness of online employee reviews

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL
Jenelle A. Morgan, Derek S. Chapman
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引用次数: 0

Abstract

Employee reviews on platforms like Glassdoor and Indeed significantly influence organizational attractiveness of millions of prospective applicants. To deepen our understanding of this phenomenon, we examined the effects of employee review characteristics on perceived helpfulness – a proximal indicator of adopting shared information. Specifically, we investigated the relationship between the sentiment of organic Glassdoor reviews (ranging from positive to negative attitudes) and their helpfulness ratings. Additionally, we explored the moderating roles of overall corporate ratings and employee status in shaping the impact of employee reviews.

Employing automated text analysis with Latent Dirichlet Allocation (LDA) and Structural Topic Modeling, we further delved into employee review content to extract the topics discussed and how their attributes (e.g., the extent to which the topic is discussed) influence perceived helpfulness. Drawing insights from an extensive analysis of 24,687 Glassdoor reviews, our findings revealed that negative reviews of lower rated organizations tend to receive higher helpfulness ratings, particularly when provided by former employees. The topics identified through LDA encompassed both instrumental and symbolic aspects of organizations, with their extent of discussion uniquely interacting with sentiment. Our study sheds light on the profound impact of employee satisfaction on the perceived helpfulness of online reviews. By presenting a comprehensive analysis of online reviews, this research offers valuable insights for businesses to enhance their organizational attractiveness and better understand the dynamics of online reputation management.

研究在线员工评论的特点和有效性
Glassdoor 和 Indeed 等平台上的员工评论极大地影响了数百万潜在求职者的组织吸引力。为了加深对这一现象的理解,我们研究了员工评论特征对感知有用性(采用共享信息的近似指标)的影响。具体来说,我们研究了 Glassdoor 有机评论的情绪(从积极到消极的态度)与其有用性评级之间的关系。通过使用潜在德里希特分配(LDA)和结构主题模型(Structural Topic Modeling)进行自动文本分析,我们进一步深入研究了员工评论内容,以提取所讨论的主题及其属性(如主题讨论的程度)对感知有用性的影响。通过对 24,687 条 Glassdoor 评论的广泛分析,我们的研究结果表明,对评级较低的组织的负面评论往往会获得较高的有用性评分,尤其是由前员工提供的评论。通过 LDA 确定的主题既包括组织的工具性方面,也包括组织的象征性方面,其讨论程度与情感有着独特的互动关系。我们的研究揭示了员工满意度对在线评论有用性的深刻影响。通过对在线评论进行全面分析,本研究为企业提高其组织吸引力和更好地了解在线声誉管理的动态提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
7.80
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