Research Interests
My research at INCAE Business School has focused on five areas: Artificial Intelligence and Machine Learning Applications, Data Science for Business Insights, Digital Transformation and Strategic Change Management, Sustainable Business Practices and Innovation, and Educational Tools and Case Study Development.
The Evolution of Sustainable Business Discourse: A Topic Modeling Analysis of Academic Literature Before and After the SDGs
Submitted and accepted to the BALAS 2025 Annual Conference in San Jose, Costa Rica (April 2025). We conducted topic modeling analysis on 4,351 academic abstracts (1979-2024) to track the evolution of sustainable business discourse pre- and post-SDG adoption. We developed a methodology combining Latent Dirichlet Allocation with AI-assisted qualitative analysis to identify and compare 15 topics in each period. We found a significant shift from foundational CSR concepts to more sophisticated discussions integrating data analytics, digital transformation, and circular economy principles
Automation and Augmentation through Digital Propensity Analysis: A Human-Centric Approach to Strategic Change Management
Presented at the SMLA 2024 Biannual Conference in Guadalajara, Mexico (December 2024). We developed a Digital Culture Propensity Index (PI), combining social network analysis with leadership behavior assessment across four organizations from different industries. We created a methodology to classify employees into four roles (Catalyzers, Aligned, Misaligned, and Neutralizers) for strategic change management. We provided a data-driven framework for selecting change agents and developing targeted digital transformation training programs.
Case Study on Work Models and Change Management
Submitted for review to The CASE Journal (2024). We discuss the future of work (ROT, Hybrid, WFH), change management, and the role of culture in business. We provided teaching notes for use in postgraduate Human Resources, Digital Business, and Change Management classes, leveraging GenAI frameworks for Storytelling with Data.
Paper on BI and Leadership Capabilities
Submitted for review to the Academy of Management Journal (2024). We analyzed over 4,800 academic papers using topic modeling to identify key variables in BI/AI project success. We developed and validated a survey using item response theory (IRT) and validated data readiness and numerate leadership constructs using CFA. We created a framework classifying organizations into four quadrants (data-driven, intuition-driven, instinct-driven, and delirium-driven) to guide BI/AI implementation strategies.
Case Study on Agile Project Management, Information Systems, and Boundary Objects
Revision sent for publication in JISE (2024). We discuss using ML/AI algorithms, agile project development, boundary objects, and design thinking. We developed teaching notes for use in postgraduate Information Systems classes.
Case Study: New Challenges and Opportunities for The Global Network for the Advancement of Management
Presented at the BALAS 2024 Annual Conference in São Paulo, Brazil (June 2024). We discussed insights from GNAM members on governance, participation, and expansion efforts through interviews, surveys, social networks, and Q-methodology factor analysis. We developed teaching and technical notes for use in postgraduate business classes.
R implementation of a script for semi-supervised screening of scientific abstracts using text mining and machine learning
My thesis project for completing the MSc in Bioinformatics & Biostatistics degree (2023). I developed a Naive Bayes classifier in R, achieving 66-87% accuracy in classifying 10,000 PubMed abstracts into 16 MeSH categories. I designed a text mining pipeline integrating corpus cleaning, word stemming, and document-term matrix creation for natural language processing and created an open-source codebase and agile development pipeline for future expansion into a web-based screening tool for biomedical researchers.
A proposed framework to measure business intelligence capabilities
Presented at the BALAS 2022 Annual Conference in Lisbon, Portugal (June 2022). We developed a formal conceptual framework to measure BI and leadership capabilities. We performed CFA to test our measurement model and summarized the dos and don’ts for BI projects based on the literature review and our framework.
¿Cómo lograr que las decisiones sean guiadas por datos?
Published in INCAE Business Review, 3(3), 75–83. (2022). We designed a survey to measure executives’ BI and leadership capabilities. We built a framework to classify the survey results in four quadrants and presented findings as a practical guide for executives to implement their BI projects.