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This chapter explores the relevance of critical race theory (CRT) and queer theory to the relational aspects of program evaluation. Often conceptual binaries that undergird traditional evaluation theory and practice (e.g., internal versus external evaluation, subjective versus objective analysis, observation versus intervention, and insider versus outsider positionalities) adversely influence rigid social roles between evaluator and participant limit a study's effectiveness in supporting programs for equity in contemporary school districts. To illustrate this approach, an array of problems within a program evaluation of a district-wide ethnic studies reform initiative is presented. Approaches to these challenges rooted in tenets of CRT and queer theory illustrate how the district was able to clarify goals and develop an effective implementation plan that focused on effective ethnic studies curriculum and pedagogy.

While there has been great attention directed at innovation within organisations in business contexts, there has been less focus on the role of innovation at higher education institutions. A changing and turbulent environment is also placing more pressure on universities and business schools to re-imagine, inspire and design an innovation culture. This empirical case presents the innovation leadership team’s point of view on the effect of innovation leadership when integrating the ISO 56000 series-based innovation management system at the University of Ruse in Bulgaria. Several face-to-face interviews and questionnaires are conducted to uncover gaps in innovation leadership based on a comprehensive literature review and the current state of the innovation management system. These gaps hold potential for improvement of the existing management system which are discussed, and recommendations are formulated in the conclusions section of this chapter. Taking into consideration the specific context in which this case study has evolved can help readers and other innovation leaders adapt the facts, conclusions, and lessons learned for universities and business schools. This chapter presents lessons learned and best practices by the innovation leadership team, as demonstrated in several cases at the University of Ruse ‘Angel Kanchev’, Bulgaria.

A quick search of the headlines of major newspapers reveals a treasure trove of technology procurement gone wrong. While the private sector seems to adopt and implement new technology seamlessly and quickly to deliver for customers, the government struggles to accomplish technology purchases and integrations with the same ease. As governments in the United States are looking to retain their current workforce and attract the next generation of workers, the technological capabilities and ethos of governments will be paramount. With nearly every industry being transformed by technology and Generation T being the first generation to have an ingrained “technology first” mindset, the ability of governments to attract these workers depends, in large part, on the ability to transform their government technology culture, policies, and practices.

In this chapter, the authors examine the administrative branch and observe two key components at the root of most technology failures: poor organizational structure in the bureaucracy and the lack of an empowered Chief Information/Technology Officer. Building upon case studies from Massachusetts and California, this chapter looks at the factors related to failure or success to understand the technology procurement culture. The chapter concludes by presenting four key “best practice” principles of public policy and administration that can be implemented by almost any governmental entity to improve their acquisition and implementation of technology.

Sherwood Forest is a mosaic of heritage, habitats and stakeholder relations. Scheme Manager, Steve Little, and Senior Lecturer in Museum Studies, Charlie Gregson, share their story of developing a working methodology in this complex landscape. By evaluating their relationship through the lenses of knowledge brokering and collaborative mentoring, they identify six themes relating to how their working environment evolved and functioned. Discussion finds significant overlap between collaborative mentoring, KE and the attainment of the Sustainable Development Goals in their ability to enable more nuanced and holistic changemaking that is contextualized in a deep understanding of need.

Knowledge brokering, a process by which an individual (or an organization) supports the transfer of research evidence into policy and practice, can improve evidence-based decision-making through knowledge exchange (KE) but is, on the whole, poorly defined in academia (Cvitanovic et al., 2017). This chapter seeks to contribute to the ‘necessary and urgent’ need for evaluation of KE in practice (Rycroft-Smith, 2022) by providing edited snippets of dialogue, analysis and key learning points. It is intended as inspiration and encouragement for academics, professionals, students and volunteers developing human-centric projects or design-thinking methodologies between universities and external partners.

Alain Verbeke is one of the world’s leading thinkers on international business (IB) and globalization, a renowned scholar and educator who contributes to creating a better global business environment by addressing some of today’s most critical challenges. He was one of the first scholars to advance a theoretically rigorous and practically significant perspective on international corporate social responsibility (CSR). Verbeke’s work on international CSR is particularly impactful because it is rooted in IB theory and based on a realistic set of assumptions about the behavior of managers, policymakers, and other market and nonmarket stakeholders. In this chapter, the authors apply theoretical principles central to Verbeke’s research – most notably behavioral assumptions of bounded rationality and bounded reliability – to analyze businesses’ and societies’ pace of progress in relation to stated environmental, social, and governance (ESG) goals. The authors argue that bounded rationality and reliability challenges create misalignment between stated/imposed commitments toward ESG performance, and economic actors’ ability to deliver on these commitments. The authors discuss examples of such misalignment, focusing on tensions among stakeholders, between stakeholder organizations and firms, and within firms. The authors propose that to be relevant for policy and practice, the sustainability research should be based on realistic microfoundational assumptions.

The chapter explores the possibilities related to using ChapGPT in tax education. Specifically, we address how tax has historically been taught in higher education and how the use of new and developing artificial intelligence (AI) tools such as ChatGPT can enhance this process going forward. The key takeaway is that AI tools are just that – tools. While tools can be effective in the problem-solving process, they are not a substitute for natural intelligence. Some basic level of subject matter knowledge is necessary to formulate the appropriate question or prompt at the beginning of the process. Additionally, a certain level of subject matter knowledge is needed to ensure that the response ultimately generated by the technology is logical, makes sense, and most importantly, provides the information necessary to appropriately address the problem at hand.

This chapter provides preliminary evidence to show that financial accounting students would use generative artificial intelligence (AI) tools to improve their learning if given the opportunity to do so by their instructors. Most students who completed the exercises we used in the study did so diligently and modified their answers after using a generative AI tool in a manner that suggests beneficial effects. It appears that the more prior knowledge a student had about the subject matter, the more beneficial was the experience. Pitfalls still exist, however. For example, students without knowledge of the subject matter struggled with crafting queries and judging the efficacy of their answers. Moreover, although a minority, some students tended to duplicate their original answers without utilizing the responses generated by the generative AI tool. Additionally, certain students merely copied the answers generated by the AI tool without providing any additional critique or analysis. Implications for teaching and learning and opportunities for future research are discussed.