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This study aims to validate a data collection tool's psychometric properties to explore whether business management research's relevance is a high-order construct made up of its perceived interest and perceived relevance. The authors conducted a confirmatory factor analysis to validate a two-factor scale. The sample was composed of 148 MBA students from a Peruvian business school. Results showed the appropriate levels of validity and reliability and confirmed the usefulness of this data set for exploring the relationship between perceived interest and relevance. Businesses and schools can replicate the validated tool for reviewing their curricula and teaching practices, exploring the gap between business and management research results and advancing managers' research literacy and evidence-based practice in business education and training.

Transnational routes such as direct-entry have become a more attractive option for Chinese students, due to the pandemic-imposed travel restrictions in China. The rise of Chinese direct-entry students can potentially lead to a significant increase in demand for academic and non-academic support not only after their arrival, but also before their departure from China. By applying Schlossberg's transition theory, this paper seeks to develop a good understanding of the academic and social belonging of Chinese direct-entry students in the UK through re-analysing the portraits (written narratives) of a previous research project. The findings indicate that these students were feeling disconnected from the academic and social communities. The factors affecting their sense of belonging are described using the 4S framework, namely self, strategies, situation and support. The paper ends with recommendations to key university stakeholders on how the partner institutions in China and the UK can help enhance a sense of academic and social belongingness of Chinese direct-entry students.

Businesses and other organizations across the globe are becoming more and more data-driven, using a combination of descriptive, diagnostic, predictive and prescriptive analytics to gain a strategic advantage through understanding the past, what we hope to happen in the future, and the ability to accurately predict future outcomes. These forms of analytics span from basic statistical summaries and data visualization to artificial intelligence models. Many organizations are now requiring new job applicants, new hires, and existing employees to be data literate. As such, it is becoming incumbent on teachers, students, and practitioners to possess some basic knowledge or experience in business analytics, at least within their educational and functional domains. Current best-practice in business school curriculum embeds some form of analytics across the curriculum. Unfortunately, many business colleges do not have the experience or resources to do so, hence teachers are unprepared to teach, and students are not prepared to enter the business world being data literate. While higher levels of analytics can be statistically intimidating, there are numerous applications of analytics that do not require statistics or higher-level models. This paper introduces one such technique practiced within marketing education and industry since 1995 and is called RFM. RFM has long been known in marketing curriculum and practice but has seen virtually no exposure in business schools outside of marketing major courses. This reflects an unintended consequence of teaching and learning within "functional" silos. It is hoped that teachers and students across the business curriculum, as well as workforce participants, can use this case to gain an appreciation of data literacy and analytics toward application within any functional area of business. The purpose of this paper is to avail those outside of marketing education and practice with an effective, easy to understand, easy to apply model, with no statistics involved. The goal is to facilitate increased data literacy and interest in understanding and/or applying analytics to other functional arear of business. RFM is not unique to this paper but is aimed at broadening teacher, student and workforce participant experience and knowledge of business analytics.

Campus-community partnerships are integral to community-engaged learning, service-learning and similar pedagogies that extend project-based learning beyond the classroom into "real world" communities. Community-engaged courses have increased in prevalence in engineering education. Evidence suggests that they are effective at connecting engineering theory to practice, engaging students motivated to "make an impact," and preparing students for global and multicultural collaboration. In community-engaged courses, campus partners (students, faculty, staff) and community partners (individuals or organizations from non-academic communities) collaborate on an engineering project that, if successful, benefits community members and contributes to student learning. However, partner relations are not always a primary focus, and partnerships can flounder and fail resulting in limited or imbalanced outcomes, dissatisfaction among partners, or even harm. Building upon documented principles for community engagement and frameworks such as critical service-learning, this paper directs attention to the relationships between campus and community partners as a crucial yet under-studied aspect of engineering community-engaged learning. We interviewed 22 campus and community partners involved in engineering projects spanning seven engineering colleges and five continents. The findings are presented in the form of a Partnerships Compass with guiding questions for nurturing partnerships that are both impactful (in achieving partners' collective goals) and equitable (in attenuating power imbalances, unequal risks of harm, and outcome disparities between partners). Ultimately, the paper aims to provide a timely perspective and actionable tool for engineering instructors, students, and community partners who aim to jointly build enduringly equitable and impactful partnerships.

In higher education institutions, critical race theory (CRT) is known to be associated with fields that study racial disparities or systemic oppression such as law, education, and ethnic studies. The impression that CRT is unrelated to fields like business or computer science may have led scholars and practitioners from these disciplines to put their focus on elsewhere than on racial inequality and its implication in their research and practice, despite apparent need. To counter such fallacy, this review article--focusing primarily on the US context--discusses CRT literature in fields where its presence is less known which are nevertheless among the major domains of higher education institutions: health sciences, computer science and information technology, sports, business, and religion. By discussing example research of how scholars have utilized CRT in different fields to challenge the race-neutral thinking that often obscures structural racism, this paper exposes racism's ability to alter manifestations and to appear through various shapes and forms within the higher education context. Initial recommendations on how educators may engage in further discussions or actions will also be considered. This paper concludes that racist ideologies are often hidden behind discipline-specific vocabulary or technical language, and it is by tackling the ideologies at work underneath the technicalities can we address the chameleon-like nature of racism more effectively.