To fully leverage the abundance of data and how data enhances decision-making, people must be data literate. Data literacy (DL) encompasses a set of interrelated skills in data management, data analysis, and the ability to interpret and communicate the results. Measuring an individual's DL level is an important first step toward designing and developing educational programs to improve one's DL skills. This paper considers a DL measurement scale referred to as the Global Data Literacy Benchmark survey and then explores the underlying constructs of this instrument. Data gathered from 311 university students across five universities in the United States is analyzed to identify and interpret the underlying factors of this DL scale. Also, the differences in DL scores among various subgroups of the students are investigated. The results show the existence of three DL factors. Also, the DL scores vary considerably among students depending upon the study areas and the comfort levels with data and analytics.

As the importance of Information Technology (IT) has exploded in business, its prominence in senior leadership teams has become pervasive. However, the success of these companies' efforts is mixed. This research uses Return on Assets, Tobin's q, and Market‐to‐Book value, to evaluate the impact of adding IT leaders into the C‐Suite (CxOs). We examine instances of a CxO as a member of the top‐five compensated executives from 1992 and 2018, identifying 2056 observations, and find that firms with a CxO have better financial performance than their non‐CxO peers. Second, different CxO titles lead to different financial impact on the firm.

Nonprofit organizations face increased competition in their volunteer recruitment efforts. Rapidly changing generational demographics within the US and an expanding base of digital marketing sources challenge the effective management of this critical process. Furthermore, many nonprofits lack the data and/or technical skills necessary to organize, analyze, and evaluate their volunteer recruiting processes. This study leverages legacy system data from two Midwest Big Brother Big Sister locations and finds that compared with Millennials, Boomers (2.08/1.63 times) and Gen-Xers (1.53/1.20 times) are significantly more likely to volunteer. Regression models revealed the significant influence of marketing sources by generation, providing insight for segmented marketing strategies. Findings also suggest an increased focus on marketing to Millennials results in overall lower volunteer rates. This article profiles an approach using basic dimensional data analysis and more advanced data analytics and serves as a guide for nonprofits to follow to develop insight into their volunteer recruitment efforts.