Sentiment analysis and the impact of employee satisfaction on firm earnings

Prior text mining studies of corporate reputational sentiment based on newswires, blogs and Twitter feeds have mostly captured reputation from the perspective of two groups of stakeholders – the media and consumers. In this study we examine the sentiment of a potentially overlooked stakeholder group, namely, the firm’s employees. First, we present a novel dataset that uses online employee reviews to capture employee satisfaction. We employ LDA to identify salient aspects in employees’ reviews, and manually infer one latent topic that appears to be associated with the firm’s outlook. Second, we create a composite document by aggregating employee reviews for each firm and measure employee sentiment as the polarity of the composite document using the General Inquirer dictionary to count positive and negative terms. Finally, we define employee satisfaction as a weighted combination of the firm outlook topic cluster and employee sentiment. The results of our joint aspect-polarity model suggest that it may be beneficial for investors to incorporate a measure of employee satisfaction into their method for forecasting firm earnings

Impact of specific CSR activities, executive & board diversity on equity valuations

Thesis (M.S.) University of Alaska Fairbanks, 2018The objective of this study is to identify the impact of specific corporate social responsibility behaviors on equity prices. This study uses fixed effect parametric and nonparametric regressions to quantify the effect of specific corporate social responsibility activities on the equity price multiples of a number of US firms from 1999 to 2009. The results of these empirical models consistently show that CEO diversity, corporate charitable giving, and work-life balance benefit plans, are associated with lower equity price multiples compared against similar firms that lack these characteristics. Additionally, board diversity and support of the LBGTQ community is associated with a positive impact on equity price multiples. This study provides evidence that individual corporate social responsibility activities can have drastic impacts on equity prices, leading the way for future research testing whether the magnitudes of these impacts are rational and in-line with their expected impact on financial performance and risk, or a deviation from the efficient market hypothesis

The Two Faces of Unionism

Our research demonstrates that the view of unions as organizations whose chief function is to raise wages is seriously misleading. For in addition to raising wages, unions have significant non-wage effects which influence diverse aspects of modern industrial life. By providing workers with a voice both at the workplace and in the political arena, unions can and do affect positively the functioning of the economic and social systems. Although our research on the non-wage effects of trade unions is by no means complete and some results will surely change as more evidence becomes available, enough work has been done to yield the broad outlines of a new view of unionism.

Employee Satisfaction and Corporate Performance: Mining Employee Reviews on Glassdoor.com

In recent years, Big Data has created significant opportunities for academic research in a wide range of topics within the social sciences. We contribute to this growing field by exploiting the unique social media data from Glassdoor.com. We extract anonymous employee reviews for textual analysis to reveal the relation between employee satisfaction and company performance. Using categories from corporate value studies, our analysis not only provide a “bird’s eye view,” but also provide specific aspects of employee satisfaction are responsible for driving these correlations. We found that while Innovation is the most important category for technology industry, Quality category drives retailing and financial industry. We confirmed the significant correlation between overall employee satisfaction and corporate performance and discovered categories that are negatively correlated with performance: Safety, Communication and Integrity. We hope that this research encourages other researchers to consider the rich environ that a text analytics methodology makes possible

Findings for the Cleveland Achieve Model: Implementation and Early Impacts of an Employer-Based Approach to Encourage Employment Retention Among Low-Wage Workers

An on-site retention program at long-term nursing care facilities had little effect overall on retention of low-wage employees, aside from a small increase in retention in the short term and among subgroups with particularly high turnover rates

Employee Satisfaction and Stock Performance

This study aims to explore the previously documented relationship between employee satisfaction and superior stock returns. Previous research suggests that firms with higher employee satisfaction also deliver superior stock returns. Furthermore, previous research has established a logical connection from employee satisfaction to superior stock performance. This study constructed an equally-weighted portfolio of the publicly traded companies on Fortune’s “100 Best Companies to Work For” list. This performance was compared to the performance of the S&P 500 on a total return basis for the calendar years 2015, 2016, 2017, 2018, and 2019. The study also collected fundamental data related to each individual companies’ firm performance and the average firm performance of companies in the S&P 500. The fundamental data collected included return on equity, profit margins, sales growth, and the price to earnings ratio. The results of this study suggest that companies with higher employee satisfaction still deliver higher stock performance and that the anomaly has not been arbitraged away by investors

Workplace Productivity Through Employee Sentiment Analysis Using Machine Learning

Purpose: The objective of this study was to analyze workplace productivity through employee sentiment analysis using machine learning.   Theoretical framework: A lot of literature is already published on employee productivity and sentiment analysis as a tool, but the study here is intended to address the issues in employee productivity post-COVID’19.   Design/methodology/approach: The authors have studied the relationship between sentiments and workplace productivity post-COVID- 19. Sentiments were captured from the text inputs given by seventy-two survey respondents from a mid-sized consultancy firm and correlated against the productivity scores. A machine learning model was developed using Python to calculate the sentiment score.   Findings: 98.6% of the respondents had a high productivity score, whereas 88.9% showed positive sentiments. The majority of the responses showed a positive correlation between positive sentiments and high productivity levels.   Research, Practical and Social Implications: The study paves way for identification of action plan for productivity enhancement through sentiment analysis.   Originality/Value: No previous work on employee productivity using sentiment analysis is done till now