This study reports the implementation of a financial inclusion app for farmers in rural Colombia. Stemming from the triple helix initiative, this study aims to make public financing instruments more readily available to farmers. Through a design science research approach, the app was collaboratively conceived, designed, implemented, and evaluated. We provide this reflective design as a case study of how a combination of triple helix collaboration, design science, and agile software development contributes toward the creation of context-oriented artefacts. The app could potentially benefit rural farmers to obtain information regarding the credit access, which is traditionally delivered in face-to-face meetings with bank staff. The findings provided evidence of the benefits and ease of use of the app, including certain affordances and constraints that are perceived by farmers. Moreover, factors such as technology literacy, experience using information and communication technologies (ICT), trust in technology, age of farmers, and mediation suggest that we should consider both material features of technology and social determinants for adoption in case of designing ICTs for rural communities.

Introduction. The rapid evolution of artificial intelligence technologies affords opportunities and challenges for libraries. The study analyses the application of artificial intelligence tools for business intelligence purposes in a university library. Method. This study used artificial neural networks to extract metadata from a syllabus corpus and then applied a string-matching model to integrate the extracted data with the loan library database. Finally clustering algorithms were employed to analyse the results, providing valuable insights into resource usage patterns. Data was extracted from faculty databases from one university in Colombia. Results. This study identified the potential of integrating artificial intelligence with business intelligence tools to enhance resource management and optimise university library operations, facilitating a better alignment between academic syllabi and available materials. Conclusions. The study found that artificial intelligence tools are valuable for university libraries in optimising processes based on data analysis. This suggests that libraries should design and implement business intelligence initiatives to automate manual tasks, providing valuable information to managers and academic directors for decision-making in administrative and academic contexts.

A core challenge of a multidisciplinary and multi-organizational translational research program is to set up and promote collaboration between researchers, labs, and organizations. Although the literature has studied and provided guidelines for collaboration, little has been written on how to evaluate it in large research projects and in a practical way. This study aims to identify dimensions and barriers to evaluating and leveraging collaboration in a large translational research ecosystem related to developing phytotherapy-based cancer treatments. By applying the Collaboration Evaluation and Improvement Framework (CEIF), our paper adds value by developing a methodological design for evaluation, incorporating mixed data in a real research ecosystem. Empirical findings provide support for applying the assessment approach and show that a research project’s sustainability depends on several collaboration factors and barriers at the socio-technical, management, operational, and institutional levels. Research results provide valuable insights for managing and improving collaborative efforts in large research groups, by anticipating collaboration issues with actionable and opportune strategies that can enhance the planning process, ecosystem performance, sustainability, research outcomes, and the program’s overall success. As a result, monitoring governance, management, leadership, and social relationships throughout the different phases of a translational research program is crucial in assessing and promoting collaboration.