In today's dynamic environment, the adaptation of the accounting profession to meet actual socio-economic needs is a challenging, and yet necessary, task. This study analyzes the technical competency requirements signalled in 171 online job advertisements for accounting positions by Canadian organizations and contrasts them with the CPA Canada competency framework, which serves as the basis for the training and accreditation of professional accountants. Following a content and a cluster analysis of the job ads, three well-separated and meaningful profiles of positions are uncovered based on technical competencies that Canadian organizations required when hiring accountants: the financial reporting, the tax aggressiveness, and the performance management profiles. From a practical standpoint, this study provides the Canadian accounting professional body, as well as educators in the accounting field, with insights regarding the expectations of the job market. The study also has implications in accounting education beyond the Canadian context.

Human-centered approaches are vital to manage the rapid growth of artificial intelligence (AI) in higher education, where AI-driven applications can reshape teaching, research, and student engagement. This study presents the Human-Centered AI for Systematic Literature Reviews (HCAI-SLR) framework to guide educators and researchers in integrating AI tools effectively. The methodology combines AI augmentation with human oversight and ethical checkpoints at each review stage to balance automation and expertise. An illustrative example and experiments demonstrate how AI supports tasks such as searching, screening, extracting, and synthesizing large volumes of literature that lead to measurable gains in efficiency and comprehensiveness. Results show that HCAI-driven processes can reduce time costs while preserving rigor, transparency, and user control. By embedding human values through constant oversight, trust in AI-generated findings is bolstered and potential biases are mitigated. Overall, the framework promotes ethical, transparent, and robust approaches to AI integration in higher education without compromising academic standards. Future work will refine its adaptability across various research contexts and further validate its impact on scholarly practices.

Building on the resource-based view (RBV) perspective, we analyse the combined effects of two highly-valued organizational resources, namely information technology (IT) capabilities and human resource management (HRM) capabilities, on the competitive performance of small and medium-sized enterprises (SMEs). Three resource configurations are derived from data on 227 SMEs (121 from the manufacturing sector and 106 from the industrial services sector) through a cluster analysis. These resource configurations are labelled IT Capabilities-dominant Configuration (ITC), e-Business Capabilities-dominant Configuration (e-BC), and HRM Capabilities-dominant Configuration (HRC). This last configuration is the best-performing, followed by the e-BC, with the ITC as the worst-performing. The results also show that manufacturing and service firms are very unevenly distributed within HRC and ITC configurations, suggesting notable differences between the two sectors regarding their respective IT and non-IT capability-building. The fact that service SMEs are overwhelmingly represented (93%) in the worst-performing configuration and completely absent (0%) in the most effective configuration while displaying the strongest IT infrastructure capabilities confirms that the IT productivity paradox is aggravated in service SMEs and calls for further research on this issue.