The Relationship between Capital Structure and Profitability of United States Manufacturing Companies: An Empirical Analysis

A thesis presented to the faculty of the Elmer R. Smith College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Cuibing Wu on April 22, 2019

Influence of CEO’s Facial Emotions in Interview Videos on Firm Market Value

Facial expressions have been seen as one of the most instinctive and efficient ways in the form of nonverbal communication. The CEO provides important facial information during the interview, which links to the firm\u27s current market situation and future planning. In the literature, few studies have examined the relationship between CEO interview facial expressions and firm performance. This study explores how CEOs\u27 facial emotions impact firm market value by analyzing the interview videos from the YouTube platform. We use the FER, a CNN algorithm-based method, to establish facial emotions and build multiple regression models to predict the firm\u27s market value. Our findings show that CEO\u27s negative emotion has a significant negative impact on market value. A positive emotional swing has a positive impact on the stock price. The high CEO’s emotional swing affects investors’ confidence in the firm performance and reflects on the stock price

Market Value with CEO Interview Videos on YouTube

Social media is now deemed as the ideal relations management platform for investors and firms. Firms and chief executive officers (CEOs) are increasingly using social media to disclose information and communicate with investors. The various kinds of information that firms and CEOs disclose through social media can materially affect the capital market. Few studies had examined the effect of the CEO interview video disclosures on firm market value. In this paper, we investigate the effect of the CEO’s interview videos on social media on the firm market value using balanced panel data consisting of 1770 firm-year observations over a period of 2015-2020. Our findings provide statistically significant evidence that the CEO’s interview videos on social media platforms have a positive effect on the firm market value. We conduct a returns model and build a two-stage treatment effects model to provide additional evidence. The results are consistent with the primary model. This research is crucial to the extant literature on information disclosure and firm market value. We believe this research will fill the gap in information disclosure and social media analytics

Information Disclosure and Capital Markets: CEO Interviews Driving Firm Value

Social media is now deemed the ideal relations management platform for investors and firms. Social media may promote more timely or extended information for investors based on its advantages, such as faster and real-time information disclosure and dissemination, and cheaper and more comprehensive access (Zhou et al., 2014). Firms and chief executive officers (CEOs) are increasingly using social media to disclose information and communicate with investors (Kelton & Pennington, 2020). The various kinds of information that firms and CEOs disclose through social media can materially affect the capital market. Few studies have examined the effect of the CEO interview video disclosures on firm market value. In this paper, we propose our research question: How do the disclosure and dissemination of CEO’s interview videos on social media impact the firm’s market value? Our study seeks to conduct an exploratory empirical analysis to test the following proposition: Disclosure of the CEO’s interview videos on social media will be associated positively with increases in the firm’s market value. Our data include observations of S&P 500 firms over the period of 2015-2020. The S&P 500 is an index of the stock market. Investors use it as the benchmark of the overall market, to which all other investments are compared. To build a balanced panel data in our study, the firms must satisfy the following criteria: (1) the firms must be available in the list of S&P 500 each year over the period of 2015-2020, (2) the financial data must be available in Compustat and CRSP during the six-year period. The total number of firms in the list of S&P 500 from the year 2015 to 2020 is 625, but the number of firms appearing every year in the time frame is 389. After removing observations with missing financial data, our panel data set consists of 1770 firm-year observations (including 295 firms) over the period 2015-2020. To collect the CEO interview videos, we obtain the CEO’s name, firm name, and fiscal year from Compustat Executive Compensation’s Annual Compensation dataset. We finally collect a total of 1271 CEO interview videos during 2015-2020. We combine interview data and the firm’s financial data. The balanced panel data consists of 1770 firm-year observations including 1369 non-video disclosing and 401 video disclosing. In this study, we investigate the effect of the disclosure and dissemination of CEO’s interview videos on social media on the market value. The primary method used in our research is based on the value-relevance design, a proven research model for investigating various factors related to firm value. We conduct a staggered difference-in-differences (SDID) model based on this value-relevance model. Furthermore, we conduct additional analyses. First, we choose the value-relevance model, the price model. Then, we check into results utilizing a two-stage effect model to ensure that our results are not biased by unobserved heterogeneity or simultaneous causality. The two-stage effect model could lead to better causal interpretations of the relationships between CEO interview disclosure and firm market value. Using balanced panel data, our findings provide statistically significant evidence that the disclosure and dissemination of CEO’s interview videos on the social media platform positively affect the firm’s market value. To the best of the authors\u27 knowledge, this is the first study to investigate the influence on the company market value of the disclosure of CEO interview videos. This research is a pivotal addition to the extant body of literature on information disclosure and firm market value. It reinforces the knowledge base and underscores the importance of social media analytics in contemporary business strategies. The findings of this study fill a research gap and give businesses a strategic appreciation of the value of social media as a platform for information disclosure, particularly concerning CEO interview videos

Company Performance Improvement by Quality Based Intelligent-ERP

The purpose of this paper is to examine the extent to which the Intelligent Enterprise Resource Planning (I-ERP) System can be used in company operations. Machine learning is embedded in a decision tree algorithm to demonstrate the viability of intelligent technology in an ERP system and to enhance the quality of operations through an I-ERP system. The study consists of two steps. In the first step, the algorithm uses the decision tree algorithm to demonstrate the application of intelligent technology in an ERP system. In the second step, the proposed model analyzes four quality criteria related to company operations through I-ERP system in order to determine whether or not I-ERP has significant improvement on managers’ decisions. As a result, the use of I-EPR may improve the quality of operations, agile respond to market demand, increase the efficiency and the competitiveness in organizations. An illustration example is provided to demonstrate the application of I-ERP

Company performance improvement by quality based intelligent-ERP

The purpose of this paper is to examine the extent to which the Intelligent Enterprise Resource Planning (I-ERP) System can be used in company operations. Machine learning is embedded in a decision tree algorithm to demonstrate the viability of intelligent technology in an ERP system and to enhance the quality of operations through an I-ERP system. The study consists of two steps. In the first step, the algorithm uses the decision tree algorithm to demonstrate the application of intelligent technology in an ERP system. In the second step, the proposed model analyzes four quality criteria related to company operations through I-ERP system in order to determine whether or not I-ERP has significant improvement on managers’ decisions. As a result, the use of I-EPR may improve the quality of operations, agile respond to market demand, increase the efficiency and the competitiveness in organizations. An illustration example is provided to demonstrate the application of I-ERP

Exploring Factors Influencing Physician Selection Decisions

Selecting a physician from the physician review sites (PRS) is a challenging and complex task for patients. PRSs overload users with too many metrics, few ratings per doctor that are positively biased, and conflicts between numeric and text ratings. This paper addresses the issue of multiple ratings in the PRS application with analytical techniques of dimension reduction, such as PCA, and text mining, including Sentiment Analysis, to address conflicts between narrative and star rating. We collected and integrated patient review data from two leading PRS websites: Vitals and Healthgrades. Our findings indicate that PCA reduces the complexity of multiple rating metrics by reducing from seven metrics to one, while sentiment analysis alerts the patients to inconsistencies between numeric and narrative ratings, allowing patients to make accurate decisions. Additionally, we plan to develop an integrated dashboard website for patients to enable them to understand and use reviews from multiple websites efficiently

Design for six sigma: A review

Six Sigma is recognized as an essential tool for continuous improvement of quality. A large num-ber of publications by various authors reflect the interest in this technique. Reviews of literature on Six Sigma have been done in the past by a few authors. However, considering the contributions in the recent times, a more comprehensive review is attempted here. The authors have examined vari-ous papers and have proposed a different scheme of classification. In addition, certain gaps that would provide hints for further research in Six Sigma have been identified. As a results the rela-tionship between Six Sigma, Design for Six Sigma (DFSS), and how these two concepts support the quality system for organizational learning and innovation performance have been discussed that would help researchers, academicians and practitioners to take a closer look at the growth, devel-opment and applicability of Six Sigma in Design