Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

This study explores the impact of service robots on customer behaviour in the hospitality industry, focusing specifically on marketing - a perspective that has been underexplored in previous research. A contextualised literature review combined with bibliometric techniques was conducted through VOSviewer and R software, analysing 856 papers sourced from the Scopus database. Findings highlight a significant increase in scholarly interest in service robots after 2022. Key insights include identification of top authors, leading journals, highly cited papers, contributing organisations, influential countries, and thematic clusters. A detailed content analysis based on bibliographic networks further identifies critical research gaps. The use of both Systematic Literature Review and bibliometric techniques also adds a valuable methodological contribution. The research is limited to the marketing domain, suggesting opportunities for future studies to explore broader perspectives. Overall, this work contributes to the literature by guiding future research directions and enhancing the understanding of marketing implications in human-robot interaction.

The advancement of Artificial Intelligence, Internet of Things have led to development advanced autonomous robots which demonstrate great ability of making conscious decision. Consequently, these smart robots are considered to be a suitable replacement for human labour by many industries and service industries are of no exception. However, in many service sectors deployment of robots in place of human labour is not encouraging. Hence, an investigation is carried on the technical challenges of robots employment in service industries of one of the fastest growing economies of the world, India. These challenges were evaluated by weighted aggregated sum product assessment (WASPAS) method. The results revealed that 'Precision and Dexterity' has been perceived as the most important technical challenge followed by 'Data Security and Privacy' while 'Maintenance and Reliability' as the least important technical challenge by the experts.

Autism spectrum disorder (ASD) is a neuro developmental disorder characterised 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 least absolute shrinkage and selection operator (LASSO) regularised bat search optimisation algorithm (LBSO), to improve the predictive performance of ASD diagnosis. The LASSO-based bat search optimisation (LBSO) algorithm integrates the LASSO regularisation technique into the BSO algorithm to enhance feature selection and optimisation. 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.

In an era of rapid urbanisation, the rise of smart cities and the integration of Internet of Things (IoT) technology for smart energy management have emerged as proactive responses to multifaceted urban challenges. This paper offers a comprehensive survey that delves deep into the synergy between IoT and energy management, shedding light on their role in shaping urban landscapes and redefining energy management paradigms. The transformative impact of IoT is illuminated, with a particular focus on its revolutionary applications in shaping smart cities by revolutionising energy management and underscores the optimisation of urban functionalities and grid efficiency, while also highlighting the critical importance of data security measures and the adaptive nature of IoT system responses. By exploring the diverse applications of IoT in smart energy management for smart cities through an in-depth literature review, the potential challenges are openly discussed.

Precision agriculture is a farming management technique that uses technology such as Internet of Things (IoT), remote sensing, and information technology to improve crop yields and efficiency. To effectively utilise the resources in precision agriculture, a novel deterministic Blockchain-IoT based secure data sharing model is introduced. The system would use optimal clustering and a hybrid encryption algorithm to ensure the privacy and security of the data being shared. The new optimisation algorithm referred to as SSA-RFO, which combines the concepts of Salp swarm algorithm (SSA) and red fox optimisation algorithm (RFO) is utilised for optimal cluster head selection. Moreover, the hybrid encryption algorithm would use a combination of symmetric and asymmetric encryption to protect the data from unauthorised access. The proposed model has been validated over the existing works in terms of accuracy, specificity, sensitivity, and precision as well.

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.