Forthcoming and Online First Articles

International Journal of Services Operations and Informatics

International Journal of Services Operations and Informatics (IJSOI)

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 Articles will not be published until the final proofs are validated by their authors.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 Services Operations and Informatics (One paper in press)

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  • Big Data-Based Predictive Model for Attendance Rate of Reserve Forces Training   Order a copy of this article
    by Jungmok Ma 
    Abstract: While reserve forces are strategically important to deter war in the Republic of Korea, the training of the reservists is a challenge since they are civilians and difficult to control. In order to tackle the difficulty of predicting the attendance rate of reserve training, this paper proposes a predictive model using Big Data. The current prediction method in the military uses the last year's attendance rate, and one previous study suggests utilizing daily weather information without a systematic analysis. This paper aims to test the significance of the predictor variables in the daily attendance rate. Next, to improve the prediction accuracy of the current method, a predictive model with the volume of web search data is proposed. In the case study, statistically significant predictor variables are identified, and the proposed Big Data-based predictive model improves the prediction performance in comparison to the current method with real reserve training data.
    Keywords: big data; search query; predictive model; reserve forces; reserve training.
    DOI: 10.1504/IJSOI.2025.10071485
     

 

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