Forthcoming 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 Articles will not be published until the final proofs are validated by their authors.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 (3 papers in press)

Regular Issues

  • Design of Company Environmental Social and Governance Performance Monitoring System Based on Internet of Things and Cloud Computing   Order a copy of this article
    by Shuliang Liu, Qianyi Zeng 
    Abstract: The reliability and accuracy of data are crucial for environmental, social, and governance (ESG) performance monitoring systems. Reliable datasets provide the foundation for accurate monitoring and effective decision-making, but these systems often face challenges such as incomplete or inaccurate data and reduced analysis and prediction accuracy. This study applies internet of things (IoT) technology to achieve real-time monitoring and collection of ESG data. This paper first deploys sensors and devices to transmit the collected data to the cloud for processing and analysis, then uses Z-score method and min max normalisation to clean, pre-process, and standardise the collected data, and uses chi square test and principal component analysis (PCA) for feature extraction. The results showed that the average prediction accuracy of the data samples that met the standards was 96.3%, and the average mean square error (MSE) was 0.105.
    Keywords: Internet of Things; Cloud Computing; Multiple Linear Regression Model; ESG Performance Monitoring System; Data Collection.
    DOI: 10.1504/IJTIP.2026.10078468
     
  • Unveiling the Determinants of Cloud Computing Adoption in Sri Lankan SMEs: A Deductive Thematic Analysis   Order a copy of this article
    by Sabraz Nawaz Samsudeen, Samantha Thelijjagoda 
    Abstract: SMEs gain operational efficiency, cost savings, and flexibility with cloud computing. Cloud computing solutions are limited in Sri Lanka and other developing nations due to technical, organisational, environmental, and personal limitations. This study uses the technology-organisation-environment (TOE) framework, the technology acceptance model (TAM), and the diffusion of innovation (DOI) theory with individual-level dimensions to analyse Sri Lankan SMEs cloud computing uptake. The study included 14 SME owners, CEOs, and IT managers from various sectors. Data was analysed using Braun and Clarkes six-step procedure using deductive codes that fit the studys conceptual framework. The study found that relative advantage, compatibility, organisational preparation, top management backing, and organisational training influence uptake. Environmental pressures from competitors and trading partners boosted adoption, whereas self-efficacy, social influences, and change aversion affected individual reactions. The findings show that cloud computing adoption involves technical capabilities, strategic leadership, and individual preparation. Technology uptake and utilisation were driven by perceived usefulness and ease of use. Through adoption models, this study presents theoretical advances and gives applicable suggestions for policymakers, cloud suppliers, and SMEs top management in developing economies. Digital transformation requires specialised skills, infrastructure, and governmental incentives for Sri Lankan SMEs.
    Keywords: Cloud Computing; Technology-Organisation-Environment (TOE); Technology Acceptance Model (TAM); Diffusion of Innovation (DOI); Thematic Analysis; Technology Adoption.
    DOI: 10.1504/IJTIP.2026.10078636
     
  • Spatial Econometric Analysis of Technological Drivers and Industrial Agglomeration in South Asian Economic Growth   Order a copy of this article
    by Wenjie Chu 
    Abstract: Industrial agglomeration boosts capital flows, technological transfer, and productivity spillovers, driving economic growth. Since industry clusters are unevenly distributed, spatial econometric methods are needed to understand regional economic interactions in South Asia. A detailed econometric study examines the technical determinants and the role of industrial agglomeration in South Asian economic growth. This study examines how R&D intensity, ICT diffusion, industrial clustering, trade openness, and capital formation affect regional growth dynamics using panel data from 2000 to 2023 and advanced spatial models like SAR, SEM, SDM, and FE. Information and communication technologies, R&D spending, and industrial clustering boost productivity directly and indirectly. The best models are the SDM and the spatial fixed effects panel model, with R2 values of 0.68 and 0.70, respectively. This shows the space-coordinated growth framework is solid. Cross-country simulations show that India leads the region in technology, while less affluent nations rely more on spillover effects, highlighting geographical disparity. The model is stable according to robustness tests using weight matrices, multicollinearity, heteroskedasticity, and sensitivity analysis. Technology investments, digital development, and cross-border industrial policies are crucial to South Asias inclusive and innovative economic growth, according to the study.
    Keywords: Spatial Econometrics; Technological Innovation; Industrial Agglomeration; Economic Growth; South Asia; Spillover Effects.

 

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