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This study explores the career trajectories of Chief Executive Officers (CEOs) to uncover unique characteristics that contribute to their success. By utilizing web scraping and machine learning techniques, over two thousand CEO profiles from LinkedIn are analyzed to understand patterns in their career paths. This study offers an alternative approach compared to the predominantly qualitative research methods employed in previous research.

This study proposes a framework for analyzing CEO career patterns. Job titles and company information are encoded using the Standard Occupational Classification (SOC) scheme. The study employs the Needleman-Wunsch optimal matching algorithm and an agglomerative approach to construct distance matrices and cluster CEO career paths.

This study gathered data on the career transition processes of graduates from several renowned public and private universities in the United States via LinkedIn. Employing machine learning techniques, the analysis revealed diverse career trajectories. The findings offer career guidance for individuals from various academic backgrounds aspiring to become CEOs.

The building of a career sequence that takes into account the number of years requires integers. Numbers that are not integers have been rounded up to facilitate the optimal matching process but this approach prevents a perfectly accurate representation of time worked.

This study makes an original contribution to the field of career pattern analysis by disclosing the distinct career path groups of CEOs using the rich LinkedIn online dataset. Note that our CEO profiles are not restricted in any industry or specific career paths followed to becoming CEOs. In light of the fact that individuals who hold CEO positions are usually perceived by society as successful, we are interested in finding the characteristics behind their success and whether either the title held or the company they remain at show patterns in making them who they are today.

As a matter of fact, nearly all CEOs had previous experience working for a non-Fortune organization before joining a Fortune company. Of those who have worked for Fortune firms, the number of CEOs with experience in Fortune 500 forms exceeded those with experience in Fortune 1,000 firms.

This paper aims to examine whether firms’ environmental, social and governance (ESG) performance indicates higher quality internal controls. The authors argue that commitment to high ESG performance is indicative of a commitment to quality corporate governance and impactful ESG practices are presumed to be achieved when pursued within a system of strong internal controls.

The authors obtain financial and ESG-related information for firms on the Financial Times Stock Exchange (FTSE)-350 for the years 2010–2018. Following prior literature, the authors use audit report lag as a measure of auditor effort. Controlling for various factors that proxy for audit clients’ inherent risk, the authors hypothesize that the remaining variance in audit report lag is related to audit clients’ control risk, and test whether ESG performance explains some of that remaining variance. To measure ESG performance, the authors use two variables to proxy firm’s ESG performance, an ESG disclosure score and being listed on the FTSE4GOOD index. Thomson Reuters provides a weighted average and industry adjusted ESG disclosure score. The FTSE4Good listing status was manually collected. Random-effect GLS panel regression model is used to estimate relationships. The authors reran their regressions using the generalized linear model and the two-stage least square model and the authors used an industry adjusted audit report lag and the lagged value of ESG and FTSE4GOOD to ensure the robustness of the results.

Regressing audit report lag on different measures of ESG performance, the authors find that better ESG performance is associated with lower audit report lag. The results remain consistent when replacing ESG with FTSE4Good and applying alternative econometrical techniques. The authors also find that female board representation facilitates lower audit report lag.

This study provides an alternative methodological approach to indicate firms’ internal control quality. In addition, auditors can benefit from firms’ ESG performance/disclosure to assess their client’s governance, internal control quality and project that on the audit risk and the level of effort required.