Forthcoming Articles

International Journal of Manufacturing Technology and Management

International Journal of Manufacturing Technology and Management (IJMTM)

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 Articles will not be published until the final proofs are validated by their authors.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 Manufacturing Technology and Management (2 papers in press)

Regular Issues

  • Choice of collaboration partners by small firms: Implications of innovation type and industry sector   Order a copy of this article
    by Bonwoo Koo, Cozzarin Brian Pa 
    Abstract: The importance of collaboration for small firms has been widely discussed; however, evidence on non-technological innovation remains limited, and small firms are typically defined by employment size. This paper examines how different forms of collaboration are associated with non-technological innovation in services when small firms are instead defined by firm age. Using data from the Korean Innovation Survey, we estimate probit models and test whether the effects differ by firm size. We show that the definition of small materially changes conclusions about which partners matter: young firms rely relatively more on horizontal and institutional partners than SMEs defined by employment size, especially for non-technological innovation. We also find that the role of vertical partners differs between technological and non-technological innovation and between manufacturing and services. Overall, the results point to the need for sector- and innovation-type-specific frameworks when evaluating collaboration outcomes.
    Keywords: small and medium-sized enterprises (SMEs); start-ups; non-technological innovation; service sector.
    DOI: 10.1504/IJMTM.2026.10081402
     

Special Issue on: Big Data and AI for Process Innovation in the Industry 4.0 Era

  • Research on total amount prediction of import and export trade data based on combined predicting model   Order a copy of this article
    by Jianxin Chen, Xiaoke Zhao 
    Abstract: In order to overcome the problems of low index significance, low prediction efficiency and low prediction accuracy in the process of prediction of import and export trade data, a new research method for total amount prediction of import and export trade data based on combined prediction model. Combine neural network prediction method and support vector machine prediction method to build a combined prediction model. Through the back propagation process, it can reduce the error between the expected and the actual output, and modify the network threshold and weight, so as to realize the classification of samples in high-dimensional space in support vector machine, and the two methods are combined to complete the prediction of total import and export trade data. The experimental results show that the significance of the proposed method is close to 100%, the prediction time is within 0.5 min, and the prediction accuracy is more than 90%.
    Keywords: Combination predicting model; Import and export trade; Data predicting; Influencing factors.

 

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