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 Articles will not be published until the final proofs are validated by their authors.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 (4 papers in press)

Regular Issues

  • Application of eye-tracking technology to analyse a university's corporate visual identity: the case of UCLM   Order a copy of this article
    by Marta Retamosa, Irene Aliagas, Ángel Millán 
    Abstract: Due to the current educational globalisation of education, universities must stand out from the competition. A range of corporate elements help them to do this. Neuromarketing devices are now being used to objectively test the attention paid to these corporate elements. This study analyses the attention to and awareness of the corporate logo of the University of Castilla-La Mancha in the different elements of visual identity in which it is found. For this purpose, eye-tracking technology and a questionnaire were applied. The sample included teaching and research professors and administration and services personnel. The results indicated that the logo received different levels of attention depending on the contractual relationship of the observer, despite coinciding in the positive values associated with the university. This research is a starting point that can contribute to improve the positioning strategy of the UCLM university brand.
    Keywords: university branding; corporate visual identity; eye tracking; heat map; scan path; neuromarketing; differentiation; attention; awareness.
    DOI: 10.1504/IJSOI.2024.10064208
  • Footwear and neuromarketing. The relationship between thermoregulatory properties and consumer perceptions   Order a copy of this article
    by David Juarez, Saray Ricote-López, Mónica Sanchís-Molla, Francisca Arán-Ais, Ana Mengual-Recuerda 
    Abstract: The thermal comfort of footwear is an essential property to ensure comfort, and an aspect that is increasingly sought by consumers. The existence of an inadequate microclimate inside the footwear can cause the destabilization of the foot-shoe system, damaging the mechanical characteristics of the foot tissue or even the motor skills of the individual. The general objective of this work is to analyse the thermoregulatory properties of safety footwear for adults, based on thermal insulation and resistance to water vapour, and to compare the results with the users' perceptions of thermal comfort. This is achieved using neuromarketing biometrics and analysing the influence of different design styles. The perception of thermal comfort in safety footwear in classic and casual styles has been analysed. The results differed according to the design used in the footwear and the predisposition to comfort of the users.
    Keywords: Footwear; thermal comfort; design; style; neuromarketing; biometrics; GSR; galvanic skin response; EEG; electroencephalography.
    DOI: 10.1504/IJSOI.2024.10064500
  • Impact of Cloud Computing Features on the Adoption of Knowledge Management Platforms   Order a copy of this article
    by Saurabh Mittal, Arpana Kumari, Sudhir Rana 
    Abstract: The role of cloud computing enabled knowledge management has come to the forefront in the last decade. The anytime-anywhere access to these solutions has made knowledge sharing and interactions easy for the employees. Organisations have found that cloud based knowledge management solutions provide more flexibility to the users and it also results in the positive impact on their behaviour thereby enhanced productivity. This paper analyses the impact of cloud computing on the employee's adoption for knowledge management platforms. This paper presents a framework for analysing the impact of cloud computing features on the acceptance of knowledge management system by the employees. The findings of this research are based on the analysis of feedback of 486 working professionals, using knowledge management systems, using structured questionnaires for the validation of the framework using structured equation modelling. The research outcomes may be utilised by the consulting organisations and organisations planning to adopt new knowledge management systems.
    Keywords: Knowledge management systems; knowledge management; KM practices; Cloud based knowledge management; Cloud for Knowledge Management.
    DOI: 10.1504/IJSOI.2024.10064734
  • Autism Spectrum Disorder Prediction using LASSO regularised Bat Search Optimization   Order a copy of this article
    by Keerthi Guttikonda, Ramachandran G., Prasad G. V. S. N. R. V. 
    Abstract: Autism Spectrum Disorder (ASD) is a neuro developmental disorder characterized by persistent social interaction, communication impairments, restricted and repetitive behaviour patterns. Early and accurate diagnosis of ASD is crucial for effective intervention and support. Over the past decade, Machine Learning (ML) techniques have shown promise in aiding ASD diagnosis by leveraging large-scale datasets and identifying clinical data patterns. This paper proposes an improved swarm algorithm, a LASSO regularised Bat Search Optimization algorithm (LBSO), to improve the predictive performance of ASD diagnosis. The LASSO-based Bat Search Optimization (LBSO) algorithm integrates the LASSO regularization technique into the BSO algorithm to enhance feature selection and optimization. LASSO effectively reduces the impact of irrelevant or redundant features, promoting sparsity and improving model interpretability. The BSO algorithm, inspired by the echolocation behaviour of bats, offers efficient search and optimisation capabilities.
    Keywords: Autism Spectrum Disorder; Machine Learning; diagnosis; feature selection; bat algorithm; regularisation.
    DOI: 10.1504/IJSOI.2024.10064907