RESUMEN
The literature knowledge gap addressed in the current study was to examine the extent that the skills taught in college degrees matched the job criteria employers needed. A survey was developed through a literature review and a focus group while the instrument was refined through a pilot project and the reliability was measured using Cronbach estimates. In the model, hard skills captured theories or methods taught in courses including organizational behavior, human resource management, statistics, financial math, economics, as well as technology in a group or individual projects. Soft skills identified interdisciplinary competencies taught throughout all courses such as teamwork, emotional intelligence, problem solving, and ethical decision making. Social desirability control was applied. Data were collected by surveying American undergraduate business students who were employed after the pandemic (N = 900). Descriptive statistics, correlation, and a structural equation model were used to test the hypotheses. A statistically significant multivariate model was developed with path effect sizes ranging from 46 to 96%. All exogenous soft skill indicators and most hard skill indicators had strong relationships to the endogenous dependent variables of learning effectiveness, job-skill match, and degree return on investment. Technology and quantitative skills, along with the dependent variable job-skill match, had the lowest means and medians, but the highest deviations. Supplementary Information: The online version contains supplementary material available at 10.1007/s43546-022-00404-1.
RESUMEN
The goal of the study was to identify big data analysis issues that can impact empirical research in the healthcare industry. To accomplish that the author analyzed big data related keywords from a literature review of peer reviewed journal articles published since 2011. Topics, methods and techniques were summarized along with strengths and weaknesses. A panel of subject matter experts was interviewed to validate the intermediate results and synthesize the key problems that would likely impact researchers conducting quantitative big data analysis in healthcare studies. The systems thinking action research method was applied to identify and describe the hidden issues. The findings were similar to the extant literature but three hidden fatal issues were detected. Methodical and statistical control solutions were proposed to overcome the three fatal healthcare big data analysis issues.