Research

Research Interests

Artificial Intelligence

Human-AI Interactions

Chatbots

Systems Beyond Firm Control

Data Analytics

Current Projects

LLM-Powered Text Mining

Revolutionizing text analysis with Large Language Models (LLMs). This project develops AI-driven tools to extract deeper insights from unstructured data, enhancing educational practices and customer service. By leveraging cutting-edge LLM capabilities, we’re creating innovative solutions that bridge the gap between raw text and actionable knowledge. Our research aims to pave the way for more intelligent and responsive systems in academia and industry, transforming how organizations understand and utilize textual information.

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Chatbot Performance Analytics

Advancing chatbot monitoring and evaluation through AI-powered analytics. This project develops sophisticated tools to assess and enhance chatbot performance across various domains. By applying machine learning and NLP techniques, we’re creating frameworks to analyze interactions, measure effectiveness, and identify improvements. Our research aims to establish new benchmarks in chatbot quality assurance, enabling more efficient and user-friendly conversational AI experiences. This work has significant implications for optimizing human-AI interactions in both commercial and public sectors.

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Adaptive Coding Learning

Transforming coding education with innovative, browser-based platforms. This project develops interactive environments that make programming accessible to non-technical learners, eliminating software installation barriers. By leveraging machine learning, we’re creating adaptive curricula tailored to business contexts, empowering students to turn data into insights. Our research aims to democratize coding skills in business education, preparing future leaders for a data-driven world. This work has significant implications for enhancing digital literacy and bridging the tech skills gap in industry.

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Publications

  1. Grego, M., Bartosiak, M., Palese, B., Piccoli, G. & Denicolai, S. (2024) “Disentangling the ‘digital’: A critical review of information technology capabilities, information technology–enabled capabilities and digital capabilities in business research,” International Journal of Management Reviews, 1–23. https://doi.org/10.1111/ijmr.12389.

  2. Palese, B., Piccoli, G. & Lui, T. W. (2021) “Effective Use of Online Review Systems: Congruent Managerial Responses and Firm Competitive Performance,” International Journal of Hospitality Management, Vol. 96, 102976, ISSN 0278-4319, https://doi.org/10.1016/j.ijhm.2021.102976.

  3. Palese, B., & Piccoli, G. (2020). “Evaluating Topic Modeling Interpretability Using Topic Labeled Gold-standard Sets,” Communications of the Association for Information Systems, 47, pp. 433-451.https://doi.org/10.17705/1CAIS.04720.

  4. Palese, B., & Piccoli, G. (2020). “Open Data: Evaluating Topic Modeling Interpretability Using Topic Labeled Gold Standard Sets,” AIS Transactions on Replication Research, 6, (9). DOI: 10.17705/1atrr.00052. Available at: https://aisel.aisnet.org/trr/vol6/iss1/.

  5. Piccoli, G., Bartosiak, M., Palese, B., & Rodriguez, J. (2020) “Designing Scalability in Required In-Class Introductory College Courses,” Information & Management, 57 (8), 103263, https://doi.org/10.1016/j.im.2019.103263.

  6. Piccoli, G., Rodriguez, J., Palese, B., & Bartosiak, M. (2019). “Feedback at Scale: Designing for Accurate and Timely Practical Digital Skills Evaluation,” European Journal of Information Systems, 29 (2), pp. 114–133. DOI: 10.1080/0960085X.2019.1701955

  7. Palese, B., & Usai, A. (2018) “The relative importance of service quality dimensions in E- commerce experiences,” International Journal of Information Management, 40, pp. 132-140. ISSN 0268-4012, DOI: https://doi.org/10.1016/j.ijinfomgt.2018.02.001.

  8. Ives, B., Palese, B., & Rodriguez, J.A. (2016). “Digital Data Streams for Customer Service Enhancement: Harnessing the Internet of Things,” MISQ Executive, 15 (4), pp. 279-297. Available at: https://aisel.aisnet.org/misqe/vol15/iss4/5

Research Collaborations

NIU Transdisciplinary AI Research Group

Partnering with leading scholars across different fields at Northern Illinois University to develop a better understanding of students’ AI perception and use.

Sapienza University of Rome & Rocky.AI Coaching Bot

Collaborating with Sapienza University of Rome professors and Rocky.AI to investigate soft skills development using an Artificial Intelligence coaching bot.

Funding and Grants

  • Palese, B., Recipient of the NIU 2023 Curricular Innovation Grant. The Curricular Innovation Grant Fund provides competitive grants for faculty experimentation with innovative teaching methods; Total Grant Amount: $5,500; Summer 2023.
  • Palese, B. (Co-Principal), Pickard, M. D. (Co-Principal), Jeon, Y. A. (Co- Principal), Rau, D. (Co-Principal), ” The Adoption and Use of Artificial Intelligence technologies in Business Schools: Problems and Prospects”; COB Summer Research Grant sponsored by NIU College of Business, Northern Illinois University; Total Grant Amount: 30,000$; Summer 2021.