Forthcoming Articles

International Journal of Research, Innovation and Commercialisation

International Journal of Research, Innovation and Commercialisation (IJRIC)

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 Articles will not be published until the final proofs are validated by their authors.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 Research, Innovation and Commercialisation (3 papers in press)

Regular Issues

  • The Role of Independent Scientists in Challenging Authoritarianism and Fostering Innovation   Order a copy of this article
    by Alberto Boretti 
    Abstract: This paper explores the vital role of independent scientists in contemporary society, particularly amidst trends towards authoritarianism and the growing influence of censorship highlighting the autonomy and innovation associated with this approach. The paper examines the challenges facing independent scientists in today's political climate, including censorship and suppression of dissenting voices. It outlines the multifaceted roles that independent scientists play in preserving intellectual integrity, providing alternative perspectives, driving innovation, and advocating for freedom of thought and speech. The paper finally discusses their contributions to research, innovation, and commercialisations, emphasising their ability to explore unconventional ideas, fill research gaps, and promote ethical innovation. Ultimately, independent scientists serve as critical defenders of truth and freedom in society, sustaining the moral and intellectual backbone in challenging times.
    Keywords: independent scientists; scientific inquiry; authoritarianism; censorship; innovation; intellectual integrity; freedom of thought; research; commercialisation.
    DOI: 10.1504/IJRIC.2025.10066072
     
  • Navigating Sustainability in Australia: the Interplay of Research, Innovation, Commercialisation, and the Challenge of Environmental Responsibility   Order a copy of this article
    by Alberto Boretti 
    Abstract: This paper critically examines Australia's sustainability approach, focusing on how research, innovation, and commercialisation (RIC) processes often prioritize profit over ecological outcomes. Despite promoting sustainability-driven innovation, many commercial strategies reinforce unsustainable models. Analysing how environmental narratives are shaped by policy, technology, and commercial interests within the Australian context, this work highlights the tension between RIC goals and effective environmental governance. The novelty lies in this critical examination of the commercialization pathway and its link to challenges like censorship impacting academic freedom. A reassessment of RIC is urged to ensure ecological integrity.
    Keywords: Sustainability; Systemic injustice; Environmental governance; Academic freedom; Censorship in higher education; Indigenous knowledge; Global collaboration; Environmental equity; Research; Innovation.
    DOI: 10.1504/IJRIC.2025.10071357
     
  • Adaptive Temporal Convolution Framework for Multi-Channel Sales Forecasting Through Dynamic EMA-XGBoost   Order a copy of this article
    by Yeasin Arafat, Mithun Kumar PK., Arif Hossen, Md Nurunnabi Sarker 
    Abstract: This research introduces a novel Dynamic Exponential Moving Average-XGBoost Fusion framework to address the growing complexity of multi-channel sales forecasting in modern retail environments. The increasing diversity of sales channels and their interconnected nature presents significant challenges in accurately predicting sales patterns across different platforms simultaneously. To tackle this challenge, we propose an innovative hybrid approach that integrates Exponential Moving Average techniques with XGBoost, incorporating adaptive temporal convolution to enhance pattern recognition across multiple sales channels. The framework leverages smoothing capabilities and predictive algorithms, creating a robust system capable of handling complex cross-channel dependencies. Experimental results across online, offline, and combined channel scenarios demonstrate the framework's exceptional performance, achieving 98.90% accuracy and 98.53% F1-score across all channels, significantly outperforming traditional approaches including Convolutional Neural Networks with 86.30%, Exponential Moving Average with 92.84%, Recurrent Neural Networks with 93.54%, and standalone XGBoost with 96.65%. The framework demonstrates robust performance across real-world applications.
    Keywords: EMA; XGBoost; Sales Forecasting; Sales Prediction; Time Series Data; Machine Learning (ML); Multi-Channel Sales; Adaptive Temporal Convolution.
    DOI: 10.1504/IJRIC.2025.10073445
     

 

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