BAR - Brazilian Administration Review

Objective: the study analyzes the main factors associated with innovation capacity in courts. Methods: the research design involves a qualitative investigation based on in-depth interviews with 17 judges and 13 staff members of the Brazilian judiciary. Data analysis was conducted using content analysis. Results: the study corroborates previous research on innovation capacity in the public sector and demonstrates the prominence of certain factors in boosting this capacity, namely: leadership, team behavior, collaboration, organizational resources, knowledge management, and information technology. Conclusions: the findings show that having people who are skilled in innovation methods and techniques, with available time, engagement, and participation both as team members and in leadership positions, is important for the innovation capacity of courts. This should be aligned with the collaboration of key actors to promote innovation. Understanding the ideal alignment among the study’s factors can assist in improving judicial services.

Artificial intelligence (AI) has emerged as a driving force in scientific development, influencing areas such as Administration and Public Administration, which are central themes of the publication of the Brazilian Administration Review (BAR). Despite transformative promises, AI’s appropriate and ethical use in academia still presents substantial challenges, especially for researchers who require specific skills to understand, critique, and utilize these technologies (Dwivedi et al., 2023; Susarla et al., 2023). Even though it is an important support tool to improve texts, the risks of hallucination (generating wrong information) and transformation of already written texts (plagiarism) worry the academic community. In addition, the continuous advancement of generative language models (LLMs) makes AI-written text detection tools often unreliable. AI literacy emerges, in this context, as an essential competence for researchers to deal with AI tools critically, ethically, and effectively. This editorial discusses the growing need to promote AI literacy as a fundamental prerequisite for researchers. It reflects on the impacts of this competence on the training of scientists capable of exploring AI’s potential while understanding its limitations and ethical implications. We argue that research on AI literacy should be a priority, not only as an emerging field of study but also as a central axis in preparing the next generation of researchers, ensuring the responsible use of AI in advancing knowledge.

Objective: the digital lending platform is a significant and innovative business concept in the field of financial technology. It creates a direct connection between lenders and borrowers. Scientists studied the technique by which digital lending companies use leverage. This study proposes an updated technology acceptance model (TAM) to investigate the factors influencing consumer adoption of digital lending platforms. More specifically, it examines how service quality and perceived threat influence trust development. Methods: this study employs structural equation modeling (SEM) to investigate the potential links between the underlying variables. Results: the study found that customers’ attitudes toward adoption of digital lending platforms are highly influenced by trust, perceived value, and perceived ease of use. The quality of service has a considerable impact on consumers’ perceptions of risk while using digital lending services. The generated model corresponds to the findings of previous studies. Conclusions: the findings of the continuing research are important for optimizing platform marketing strategies and translating strategic goals into concrete activities. To improve future research, we recommend integrating more variables to have a more comprehensive understanding of the adoption intentions of digital lending platforms.

Objective: this study is based on the assumption that the level of corruption in a country’s context can influence how stakeholders perceive the environmental, social, and governance (ESG) practices disclosed by companies. The objective is to analyze the moderating effect of corruption on the relationship between ESG performance and the relevance of accounting information for companies in G20 countries. Methods: the study considered 171,693 firm/year observations from organizations in G20 countries that had all the necessary data to measure the relevance of accounting information from 2013 to 2021. Descriptive analysis, correlation, and multiple linear regression were conducted. Results: based on the findings, it can be inferred that unified ESG performance, as well as its individual pillars, is positively associated with the market value of the analyzed organizations. However, when observing the moderating effect of corruption levels, no significant results were obtained. Conclusions: this study contributes to the literature and to users of accounting information by identifying that the ESG performance of G20 companies helps increase the relevance of accounting information, and that external factors, such as corruption, affect the level of ESG disclosure, but not to the extent of being significant for the market.

Objective: this study investigates the use of integrated social media (SM) technologies to support knowledge-sharing (KS) processes in information technology (IT) projects. Its main objective is to develop a framework to assist project managers in solving problems such as selecting or replacing social media tools, developing KS processes, and creating guidelines. Methods: the affordance theory was the theoretical lens adopted to explore the relationship between using technology (SM) and organizational change processes (KS). The design science research (DSR) was adopted as a prescriptive method. The work adds to the body of knowledge and provides a support tool designed and validated specifically for practitioners and researchers. A literature review served as the basis for creating the framework, and 18 interviews with IT project members helped assess and refine it. Results: the resulting framework consists of three components based on affordance perception, materialization, and effect. It is presented from both component and integrative complementary views and has the potential to contribute to solving problems identified in the literature and in practice. Conclusions: the successful application of the framework in IT projects can promote the benefits of KS, potentially increasing management effectiveness and positively influencing outcomes.