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This research explores whether Glassdoor's annual rankings of the Best Places to Work provide meaningful information to shareholders in identifying companies with the potential for superior future performance. Because their website reaches over 64 million unique visitors monthly, Glassdoor rankings can influence trading patterns. Glassdoor’s awards offer a unique way to analyze employees' feedback as there is no self-nomination process or cost involved, differentiating it from other measures of job satisfaction such as Fortune’s Best Companies to Work For survey.

We compare holding period returns of the Best Companies firms to the performance of the S&P 500 index and three separately constructed matched benchmark portfolios. We calculate cumulative raw, risk-adjusted, and abnormal returns based on a buy-and-hold strategy as well as by using the Fama-French (1993) 3-factor and 4-factor models. We also analyze whether selected companies have higher performance one year after the announcement. We control for possible endogeneity problems.

We find mixed evidence regarding the superiority of the Best Company firms in holding period returns and risk-adjusted measures compared to appropriate benchmarks. Longer-term cumulative raw returns show that they have higher annual returns compared with its benchmarks. The differences are not statistically significant on a raw or risk-adjusted basis.

The Best Companies sample is much larger than the matched sample, even with multiple matching methodologies. This difference is limited by the survey design as the employees of larger companies tend to post in Glassdoor survey. Also, since companies in the small Best Companies sample are private companies, comparing their stock performance with comparable companies is challenging.

Human resource management theories argue that job satisfaction results in enhanced corporate performance. However, verification of such satisfaction by a Glassdoor, as a third-party survey, does not necessarily lead to higher risk-adjusted share price performance.

We extend previous work that focuses on analyzing employee reviews to consider the impact of being ranked among the best companies on the survey. Second, we employ an extended set of financial performance measures to assess impact. Our analysis also employs a wider range of financial performance metrics and robustness tests.

Firms are able to reduce financing costs and/or increase the funds available for expansion by minimizing the amount of funds tied up in current assets. We provide insights into the performance of surveyed firms across key components of working capital management by using the CFO magazine’s annual Working Capital Management Survey. We discover that significant differences exist between industries in working capital measures across time. In addition, we discover that these measures for working capital change significantly within industries across time.

Each year since 1983, Fortune magazine has published a survey featuring “America's most admired” corporations. Although the most admired corporations are certainly worthy of some praise and the least admired deserving of criticism, whether these admired companies are worthy of investors' money is less clear. We examine the ex ante and ex post returns of a sample of the most and least admired corporations in the Fortune survey.

Faculty internships in family business offer potential benefits to faculty, students, and the community by blending academics with real world business. The purpose of the paper is to report how faculty internship experiences in family businesses enhance the goals of continuous improvement of curriculum and research output in a business school. The University of Toledo Center for Family Business embarked on a pilot faculty internship program during the summer of 1998. We detail the back ground for the Stranahan Faculty Program at the University of Toledo, discuss the program implementation, and report the final organizational level assessment.

This research explores the effect of supply chain disruptions on competitors. Using companies in the automobile industry, we study the contagion effect in supply chains based on the affected firm and its competitors, whether the disruption occurs domestically or by a foreign-based firm, and within the context of economic market cycles.

Standard event study methodology is used to test the stock price reaction to supply chain disruptions. The purpose of this methodology is to determine whether the announcement of an event produces a “significant” stock price reaction around the time of the announcement. To conduct such tests, daily stock returns are measured around the announcement date and compared with the expected return. To further test whether the event study results can be explained by the business cycle, sample period, and stock characteristics, we use regression analysis. Our analysis is based on a data of 408 disruptions compiled from news announcements.

Supply chain disruptions have consequences for affected companies as well as competitors. The stock market impact from disruptions in automobile companies is affected by market cycle as well as the brand domicile. We observe that negative stock effect of disruptions occurs in bear markets but not in bull markets. American-brand automakers experience a larger stock price decline in bear markets compared to Japanese-brand automakers. Our results support a contagion effect as American-brand automakers experience negative stock reactions when a competitor announces disruptions. The contagion is more pronounced for American-brand automakers in bear markets when disruptions are announced by Japanese-brand automakers. We do not find evidence of a contagion effect for Japanese-brand automakers, indicating that they may be more resilient and are not affected by competitors’ supply chain performance.

The U.S. automobile industry is dominated by five major firms. While our research is ground-breaking, the ability to generalizing to other industries that are less concentrated in leadership and competition may be limited.

Our study has implications for supply chain managers who make decisions regarding investments in disruptions mitigation. The results are also of interest to investors who may seek opportunities to take short positions on stocks within the automobile industry.

Our paper is the first to test the impact of supply chain disruptions on competitors. Additionally, we characterize the impact of disruptions based on market cycle and company domicile.

Jim Collins' Good to Great is but one of many popular press books on management. In his book, Collins discusses the keys to success for today's corporations. Many managers flocked to bookstores to discover what they might be missing in making their organization great. This paper aims to use methodologies more commonly found in the finance literature to validate the results of Collins' study.

This paper uses methodologies more commonly found in finance literature (e.g. event study methodology, Fama‐French three‐factor model with momentum, buy‐and‐hold abnormal returns) to validate the results of Collins' study.

The results show that the Good to Great firms had unexceptional performance when compared to other benchmark lists of firms, on an ex‐ante or ex‐post basis.

From a management perspective, the advice that one might obtain from Good to Great should be carefully examined by managers before they implement it, only to find that great is not really so great.

The paper is original in its methodological design and is valuable to managers who are seeking advice for opportunities that enhance shareholder wealth.

The purpose of this paper is to examine whether community banks have gained market share at the expense of larger, regional banks in small metropolitan statistical areas (MSAs). The authors also seek to examine market share gains of community banks relative to each other.

The empirical research is conducted using deposit and market share data for community and regional banks between 2001 and 2008. The authors employ regression analysis.

It is found that community banks have gained market share. When regional banks are excluded and the market share gains of community banks relative to each other examined it is found that community banks with lower market shares gain relative to banks with a larger initial share of the deposit market.

Research is conducted using eight metropolitan statistical areas (MSAs) in Wisconsin, Minnesota, and Iowa. Thus, conclusions drawn are based on analysis conducted in one region of the United States.

The paper's findings are in contrast to traditional thinking about size and market share and suggest that community bank managers should focus on each other as well as regional and mega‐bank competitors.

The paper uses market share as a proxy for bank size as a means of explaining the competitive landscape that exists within community banking.

This study examines the market reaction when announcements of large dividend increases are made by more versus less rate‐regulated firms in the same industry. The insurance industry was chosen because property/liability insurers are rate‐regulated more than life/health insurers. The abnormal returns are positive and significant for all insurers but smaller than those found in previous cross‐sectional studies. Abnormal returns for the less rate‐regulated life/health insurers during the dividend increase announcement period are significantly greater than those of the more rate‐regulated property/liability insurers.

This study aims to systematically review various behavioral biases that impact an investor’s decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors’ behavior.

Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.

This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors’ decision-making. Through thematic analysis, an attribute–consequence–impact framework is proposed that explains different biases leading to individual investors’ irrationality. The study further proposes directions for future research by applying the theory–characteristics–context–methodology framework.

The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.

The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor’s decision-making.

The purpose of this paper is to determine the factors influencing managers’ decision to adopt cloud computing in the UK using the “Technology-Organisation-Environment” (TOE) framework.

Data were collected through a self-created questionnaire based survey that was completed by 257 mid-to-senior level decision-making business and information technology (IT) professionals from a range of UK end-user organisations. The derived hypotheses were tested using various data analysis techniques including principal component analysis and logistic regression.

The results show that four out of the eight factors examined have a significant influence on the adoption decision of cloud computing services in the UK. Those key factors include competitive pressure, complexity, technology readiness and trading partner pressure. The latter predictor; trading partner pressure, was the most significant factor for the adoption decision of cloud services reflecting organisations’ concerns on legal regulations, co-creation and customisation, service linkage and vendor locking which adds complexity to the process of selecting an appropriate vendor.

This research found trading partners (cloud service providers) significantly influence managers’ decisions to adopt cloud services, however, further research is required to fully understand all the aspects involved especially with the growing number of vendors available. Although over 250 usable responses to the questionnaire were received and analysed, there was not a sufficient quantity of responses from each industry sector or organisation size to conduct further analysis.

The findings reveal the important role of cloud computing service providers to enable end-users to better evaluate the use of cloud computing. It also reveals that top management support is no longer a driver as organisations are starting to adopt cloud computing services on the basis of cheaper and more agile IT resources in order to support business growth.

This research provides original insight for cloud computing adoption within the UK from a managerial perspective.