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Article
Publication date: 15 April 2024

Ela Oğan

Within the scope of the research, articles about service robots were examined by the systematic review method.

Abstract

Purpose

Within the scope of the research, articles about service robots were examined by the systematic review method.

Design/methodology/approach

The research aims to evaluate the articles on service robots, an artificial intelligence (AI) application in restaurant businesses, using a systematic review method. In systematic reviews, the data obtained as a result of scanning databases to find an answer to a research question are synthesized and reported. The criterion sampling technique, one of the purposeful sampling methods, was used for the sample of the research. Inclusion and exclusion criteria were applied within the scope of screening.

Findings

The articles on service robots were carried out between 2018 and 2023. In terms of research methods, most of the articles are quantitative, while there are studies on mixed and qualitative methods. In studies, data were generally collected by survey technique. The keywords of the studies on service robots are examined; the most commonly used words were service robot and AI, technology, restaurant, satisfaction, revisit intention, consumer behavior, intention, preference, hospitality and foods. The objectives of the articles pertinent to service robots are mostly to determine people's attitudes and acceptance toward these services focuses.

Originality/value

The studies seem to focus more on customer acceptance, trust, expectations, risks, adaptation, reasons for preference, impact on creative services, emotional and cognitive effects and human–robot interaction. Despite this, it is observed that there are fewer studies on topics such as the development of service robots in restaurant businesses, their reflections on the future, future opportunities and the quality of chef service robots. Based on this, it is recommended to consider studies that will serve as a reference for revealing innovative opportunities that can meet future expectations in order to increase the quality of service robots in restaurant businesses.

Details

Worldwide Hospitality and Tourism Themes, vol. 16 no. 2
Type: Research Article
ISSN: 1755-4217

Keywords

Article
Publication date: 19 July 2024

Alejandro Garcia Rodriguez, Marco Antonio Velasco Peña, Carlos A. Narváez-Tovar and Edgar Espejo Mora

This paper aims to investigate and explain the dual fracture behaviour of PA12 specimens sintered by selective laser sintering (SLS) as a function of wall thickness and build…

Abstract

Purpose

This paper aims to investigate and explain the dual fracture behaviour of PA12 specimens sintered by selective laser sintering (SLS) as a function of wall thickness and build direction with a powder mixture 30:70. To achieve this objective, research related to chemical, thermal and structural behaviours as a function of the input variables was carried out to describe and explain why ductile-fragile behaviour occurs during fractures under uniaxial tension manufactured via a methodology of material analysis and manufacturing processes.

Design/methodology/approach

The factorial design 32 relates the fracture of PA12 tensile specimens to the horizontal, transverse and vertical build directions at 2.0, 2.5 and 3.0 mm thicknesses, respectively. Fractographic images revealed the fracture surfaces and their dual ductile-fragile behaviour related to the specimens’ measured crystalline, thermal, surface and chemical properties.

Findings

The study showed that thermal property variables differ depending on the input variables. The wall thickness variable affected this morphology the most, showing the highest percentage of the ductile area, followed by the transverse and vertical directions. It was determined that the failure in the vertical direction is due to crystalline gradients associated with the layer-by-layer construction process. The pore density may be closely related to generating ductile and brittle areas.

Originality/value

In this paper, fracture characterisation is performed based on the mechanical, chemical, structural, thermal and morphological properties of PA12 manufactured by SLS. In addition, a heatmap of porosities in cross-sections is constructed using a machine learning model (k-means) related to dual fracture behaviour. This research revealed significant differences in the fracture type according to the build direction. In addition, thin-section fractography provides a more detailed explanation of the fragile behaviour of the vertical direction associated with crystalline changes due to the direction of the sintering layers.

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