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Purpose – Equally male/female-owned businesses have been a part of the United States (US) economy and provide a platform for female entrepreneurs, yet these businesses have been understudied in today’s literature. This study examines trends in the performance of equally male/female-owned firms and compares them to female-owned and male-owned businesses. In addition, through social role theory, factors beyond gender are discussed to explain the potential differences in firm performance among various firm ownership groups. Design/methodology/approach – This study uses eight years of US Census data to analyze annual trends and average firm performance for equally male/female-owned, female-owned, and male-owned firms. A one-way analysis of variance (ANOVA) is used to compare the means of the firm performance variables by each ownership group, followed by Tukey’s Honest Significant Difference (HSD) test to assess the significance of differences. Findings – The findings reveal that equally male/female-owned firms perform similarly to female-owned firms, both of which significantly underperform in sales, productivity, and pay when compared to male-owned businesses. This interesting outcome indicates that the presence of a male co-owner does not automatically translate to an increased firm performance and that factors beyond gender influence the trajectory of these businesses. Additionally, the large presence of family-owned firms within the sample of equally male/female-owned firms sheds new insight into family business literature and helps explain the comparable performance patterns with those of female-owned firms. More specifically, both ownership groups, equally male/female-owned and female-owned firms, likely prioritize nonfinancial goals, such as family and work-life integration, potentially at the expense of firm performance. Originality/value – This study is one of few to date that investigates a third firm ownership category in the US market, the equally male/female-owned firms, and compares them based on average performance to two previously studied groups, male-owned and female-owned firms. This article contributes to the body of knowledge by providing insight into the performance of equally male/female-owned businesses through the underpinnings of social role theory, as well as important implications for gender, female entrepreneurship, equal ownership, and family business policy and practice. © 2025 Emerald Publishing Limited

As companies continue to put data and business analytics as their top priority, universities will need to supply students with the appropriate skill sets that meet this demand and offer future opportunities to their graduates. Although business analytics is a new field, many of the required competencies stem from already established areas such as Information/Computer Technology or Information Systems. Using a sample of 225 randomly selected AACSB accredited business schools this study examined the new developments in Business Analytics undergraduate academic programs, and determined the amount of overlap between the Business Analytics and the Information/Computer Technology degree programs. Our findings reveal that approximately 36 percent of the Business Analytics programs overlap with the Information/Computer Technology programs. In addition, the top three required courses in most Business Analytics programs include a Database course, predictive analytics course, and Introduction to Business Analytics. This research provides valuable insight for schools that haven't adopted a Business Analytics degree yet or are looking to improve their existing curriculum. In addition, colleges and universities can now utilize the appropriate Information Systems courses and include them as important foundation and part of their Business Analytics programs.

Faculty teaching data analytics at undergraduate level are often faced with the tension created by student under-preparedness, the demands of the course, and time constraints. How do faculty close this gap? In this paper, we propose the use of flow diagramming as an accessible method for interpreting regression analyses, in ways that are time efficient and not alienating to the student. Our study shows that the use of such flow diagrams has a positive effect on student understanding without additional remedial instruction. Time saved can be directed at core learning objectives of the analytics.

Logistic regression (LoR) is a foundational supervised machine learning algorithm and yet, unlike linear regression, appears rarely taught early on, where analogy and proximity to linear regression would be an advantage. A random sample of 50 syllabi from undergraduate business statistics courses shows only two percent of the courses included LoR. Conceivable reasons for this dearth of LoR content is likely related to topic complexity, time constraints, and varying degrees of tool ease of use and support. We propose that these constraints can be countered by: [1] introducing logistic regression early, [2] informed tool selection prioritizing ease of use with comprehensive output, and [3] using/developing innovative, accessible, and easy to understand concept learning aids. This approach would leverage the proximity to linear regression and probability readily embed distributed practice for student understanding of a foundational technique.

Blockchain is being promoted as the platform to disrupt business as usual in many transaction-heavy sectors. Questions remain about the future standards of blockchain, their feature set, functionality, and the willingness of organisations to disrupt their existing revenue streams via blockchain.  The most significant near-term promise that affords industry is the cost and complexity savings via the standardization of their technology infrastructure stacks.  This paper explores the benefits available of reduced costs and complexity via the adoption of blockchain.

Successful property management, which can be done by individual owners or by professional property managers, has numerous interrelated complex business processes: tenant attraction, screening, leasing, tenant move-in, property maintenance, retention/lease renewals, tenant move-out, and reputation management. Property managers must be highly skilled communicators and thoroughly understand the legal implications of housing and contract law in their operating environments. The lack of affordable solutions available to small and mid-sized property managers drives their use of fragmented technology solutions provided by numerous technology vendors that employ redundant data-gathering methods, putting them at a competitive disadvantage. This research paper explores the information systems needs of property managers in contrast to the solutions available to them in the marketplace.

This paper introduces a universal framework for service-based learning which provides information systems students with opportunities to gain invaluable hands-on experience. More specifically, through this framework, students can develop hard, soft, and interdisciplinary skills in preparation for their first professional careers upon graduation. In addition to introducing the framework, we provide student testimonials and feedback as well as lessons learned from our experience in efforts to prepare and help other schools interested in offering similar growth opportunities to their students to have a smooth and successful implementation. © 2023, Journal of Information Systems Education. All Rights Reserved.

Free, online language translation services are being used by people around to the world to facilitate communication. However, it takes time and effort for a person to load the Web page in a browser, copy and paste text into the site, and translate words. The process quickly becomes tiresome. Instead, some computer programs are providing automated translation. However, no studies have been conducted to determine the efficiency or effectiveness of such an approach. In this study, we compare how students used an English-based chatbot with and without German automatic translation. Results show that students took nearly 1.5 times longer than their stated upper time limit to manually translate. In contrast, the automated translation was at least 30 times faster. In addition, the students were significantly more satisfied with the automated than the manual system.