@article {
    orvium-653b214601c0cebf45471cd0,
    title = "Assessing Knowledge Economy Utilization in Research at Technological Institute of the Philippines",
    abstract = "This study aims to assess how Technological Institute of the Philippines (TIP) utilizes principles of the knowledge economy in its research activities. A mixed methods approach is employed combining quantitative and qualitative analyses of research publications from TIP over the past 5 years. The publications will be collected from databases and repositories then preprocessed through text cleaning. Latent Dirichlet Allocation (LDA), a topic modeling technique, will be applied to identify prevalent themes within the publications. Both the frequency and content of topics related to knowledge economy concepts like innovation, technology transfer, and industry collaboration will be examined. In addition to quantitative metrics from LDA modeling, a qualitative analysis of publications within knowledge economy topics will provide context. The findings will offer strategic recommendations to better align TIP's research agenda with knowledge economy goals of fostering innovation, knowledge sharing, and technological progress. Proper ethical guidelines will be followed to ensure data privacy and anonymity. The study methodology integrates computational and manual approaches to comprehensively evaluate TIP's utilization of the knowledge economy in research.",
    keywords = "Knowledge economy, Research assessment, Topic modeling, Latent Dirichlet allocation (LDA), Technological Institute of the Philippines (TIP), Research publications, Text mining, Natural language processing (NLP), Mixed methods, Quantitative analysis, Qualitative analysis, Innovation, Technology transfer, Industry collaboration, University research, Strategic planning, Research alignment, Knowledge sharing, Research themes, Research trends, Computational linguistics, Text analytics, Academic institutions, Higher education, Research evaluation, Knowledge economy principles and assessment of research alignment, LDA topic modeling and text mining/NLP methods, TIP as the academic institution studied, Mixed quantitative and qualitative research approaches, Strategic insights and recommendations for research planning",
    author = "Kevin Dykes Aguila and Jan Jerome Soriano and Carlo Poblete",
    year = "2023",
    language = "English",
    url = "https://dapp.orvium.io/deposits/653b214601c0cebf45471cd0/view",
}