Forthcoming and Online First Articles

International Journal of Technology Intelligence and Planning

International Journal of Technology Intelligence and Planning (IJTIP)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Technology Intelligence and Planning (2 papers in press)

Regular Issues

  • Exploring the Evolution of Emerging Technologies using Text Mining Method based on Machine Learning: Evidence from Intelligent Ship Technology   Order a copy of this article
    by Jingyi Yao, Weiwei Liu, Kexin Bi 
    Abstract: Emerging technologies has reshaped multiple industries, notably the maritime sector, where intelligent ship technology has emerged as a pivotal innovation. However, little attention has been given to mapping its evolution. To address this gap, we introduce a framework, employing text mining and machine learning to unravel the evolution of intelligent ship technology. Our method applies LDA to identify topics over time, dissects evolution in intensity, content, and state, and maps evolution paths of topics to assess current research and forecast trends. The main findings are as follows: First, the topic distribution of intelligent ship technology gradually shows diversity over time. Second, the topic content shows crossover, penetration and integration among the research topics. Third, the evolution state presents complex evolutionary relationships of dividing, consolidating and inheritance. This extends research, offering a dynamic view of state and progress of intelligent ship technology, informing researchers, policymakers, and stakeholders to harness its potential.
    Keywords: intelligent ships; latent Dirichlet allocation; LDA model; topic identification; topic evolution analysis; technology evolution path.
    DOI: 10.1504/IJTIP.2025.10066548
     
  • The Preferences and Needs of Higher Education Students from Learning Analytics Dashboards in a Blended Learning Environment   Order a copy of this article
    by Amina Ouatiq, Bouchaib Riyami, MANSOURI KHALIFA 
    Abstract: Learning analytics dashboards improve learning outcomes, track and monitor students’ learning experiences, and help make data-informed decisions. However, most dashboards are neither intended directly for students nor designed and developed with them as users. To address this issue and provide students with suitable tools that meet their needs. The authors present an empirical study that investigates the students’ requirements and expectations when taking distance or hybrid courses. This study identifies the types of uses and functions that students require in their activities, guiding the design of a learning analytics dashboard.
    Keywords: human centred learning analytics; Learning analytics dashboard; User’s needs; Survey; Indicators; Case study.
    DOI: 10.1504/IJTIP.2025.10070077
     

 

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