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Drawing on the theory of memory-dominant logic, this study aims to examine how the substantive staging of the servicescape, experience co-creation, experiential satisfaction and experience intensification affect experience memorability and hedonic well-being in the case of unmanned smart hotels.

An online survey was used, with the target respondents being hotel guests people aged 18 years and older who had been recent guests of the FlyZoo Hotel in Hangzhou, China. Data were collected online from 429 guests who had stayed in the hotel between April and June 2023. Data analysis was undertaken using structural equation modelling.

The results suggest that all the proposed four constructs are positive drivers of a memorable unmanned smart hotel experience. The relationship between the memorability of the hotel experience and hedonic well-being was found to be significant and positive.

Unmanned smart hotels should ensure that all smart technologies function effectively and dependably and offer highly personalised services to guests, allowing them to co-create their experiences. This will lead to the guest receiving a satisfying and memorable experience. To enable experience co-creation using smart technologies, unmanned smart hotels could provide short instructional videos for guests, as well as work closely with manufacturers and suppliers to ensure that smart technology systems are regularly updated.

This study investigates the antecedents and outcomes of a novel phenomenon and extends the concept of memorable tourism experiences to the context of unmanned smart hotels.

Drawing on person–environment fit theory, this study aims to investigate how the relationships between service task types (i.e. utilitarian and hedonic service tasks) and perceived authenticity (i.e. service and brand authenticity) differ under different conditions of service providers (human employee vs service robot). This study further examines whether customers’ stereotypes toward service robots (competence vs warmth) moderate the relationship between service types and perceived authenticity.

Using a 2 × 2 between-subjects experimental design, Study 1 examines a casual restaurant, whereas Study 2 assesses a theme park restaurant. Analysis of covariance and PROCESS are used to analyze the data.

Both studies reveal that human service providers in hedonic services positively affect service and brand authenticity more than robotic employees. Additionally, the robot competence stereotype moderates the relationship between hedonic services, service and brand authenticity, whereas the robot warmth stereotype moderates the relationship between hedonic services and brand authenticity in Study 2.

Restaurant managers need to understand which functions and types of service outlets are best suited for service robots in different service contexts. Robot–environment fit should be considered when developers design and managers select robots for their restaurants.

This study blazes a new theoretical trail of service robot research to systematically propose customer experiences with different service types by drawing upon person–environment fit theory and examining the moderating role of customers’ stereotypes toward service robots.

This study aims to investigate the impact of indium (In) content on the thermal properties, microstructure and mechanical properties of Sn-3Ag-3Sb-xIn (x = 0, 1, 2, 3, 4, 5 Wt.%) solders to enhance the performance of tin-based solder under demanding conditions and to meet the urgent need for high-reliability microelectronic interconnection materials in emerging sectors such as automotive intelligent technology, 5G communication technology and high-performance computing.

In this study, Sn-3Ag-3Sb-xIn solder alloys were prepared. The thermal properties of the solder alloys were characterised by differential scanning calorimetry. Subsequently, optical microscopy, scanning electron microscopy, X-ray diffraction and an electron probe X-ray microanalyser were used to analyse the influence of the In content on the microstructure of the solder. The mechanical properties of solder alloys were determined through tensile testing.

As the In content increased, the melting temperature of the Sn-3Ag-3Sb-xIn solder decreased, accompanied by less nucleation undercooling and an expanded melting range. The incorporation of In led to an enhancement in the yield and tensile strengths of the Sn-3Ag-3Sb-xIn solder alloys, but with a concomitant decrease in plasticity. In comparison to commercial Sn-3.0Ag-0.5Cu solder alloys, the yield strength and tensile strength of the Sn-3Ag-3Sb-3In alloy increased by 8.64 and 21.69 MPa, respectively, while the elongation decreased by 11.48%.

Sn-3Ag-3Sb-3In solder alloy was the most appropriate and expected comprehensive properties. The enhancements will provide substantial assistance and precise data references for the interconnection requirements in high-strength interconnection fields, such as automotive intelligent technology, 5G communication technology and high-performance computing.

The reliability of solder joints is closely related to the growth of an intermetallic compound (IMC) layer between the lead-free solder and substrate interface. This paper aims to investigate the growth behavior of the interfacial IMC layer during isothermal aging at 125°C for Sn-3Ag-3Sb-xIn/Cu (x = 0, 1, 2, 3, 4, 5 Wt.%) solder joints with different In contents and commercial Sn-3Ag-0.5Cu/Cu solder joints.

In this paper, Sn-3Ag-3Sb-xIn/Cu (x = 0, 1, 2, 3, 4, 5 Wt.%) and commercial Sn-3Ag-0.5Cu/Cu solder were prepared for bonding Cu substrate. Then these samples were subjected to isothermal aging for 0, 2, 8, 14, 25 and 45 days. Scanning electron microscopy and transmission electron microscopy were used to analyze the soldering interface reaction and the difference in IMC growth behavior during the isothermal aging process.

When the concentration of In in the Sn-3Ag-3Sb-xIn/Cu solder joints exceeded 2 Wt.%, a substantial amount of InSb particles were produced. These particles acted as a diffusion barrier, impeding the growth of the IMC layer at the interface. The growth of the Cu₃Sn layer during the aging process was strongly correlated with the presence of In. The growth rate of the Cu₃Sn layer was significantly reduced when the In concentration exceeded 3 Wt.%.

The addition of In promotes the formation of InSb particles in Sn-3Ag-3Sb-xIn/Cu solder joints. These particles limit the growth of the total IMC layer, while a higher In content also slows the growth of the Cu₃Sn layer. This study is significant for designing alloy compositions for new high-reliability solders.

The application of industrial robots in modern production is becoming increasingly widespread. In the context of flexible production lines, quickly and accurately identifying and grasping specified workpieces is particularly important. This study aims to propose a grasping scheme that combines traditional methods with deep learning to improve grasping accuracy and efficiency.

First, a dataset generation method is proposed, which constructs a point cloud dataset close to the real scene without the need for extensive data collection. Then, the 3D object detection algorithm PointPillars is improved based on the features of the scene point cloud, allowing for the analysis of part poses to achieve grasping. Finally, a grasp detection strategy is proposed to match the optimal grasp pose.

Experimental results show that the proposed method can quickly and easily construct high-quality datasets, significantly reducing the time required for preliminary preparation. Additionally, it can effectively grasp specified workpieces, significantly improving grasping accuracy and reducing computation time.

The main contribution of this paper is the integration of a novel dataset generation method, improvements to the PointPillars algorithm for 3D object detection and the development of an optimal grasp detection strategy. These advancements enable the grasping system to handle real-world scenarios efficiently and accurately, demonstrating significant improvements over traditional methods.

Due to the complexity and diversity of megaprojects, the architectural programming process often involves multiple stakeholders, making decision-making difficult and susceptible to subjective factors. This study aims to propose an architectural programming methodology system (APMS) for megaprojects based on group decision-making model to enhance the accuracy and transparency of decision-making, and to facilitate participation and integration among stakeholders. This method allows multiple interest groups to participate in decision-making, gathers various perspectives and opinions, thereby improving the quality and efficiency of architectural programming and promoting the smooth implementation of projects.

This study first clarifies the decision-making subjects, decision objects, and decision methods of APMS based on group decision-making theory and value-based architectural programming methods. Furthermore, the entropy weight method and fuzzy TOPSIS method are employed as calculation methods to comprehensively evaluate decision alternatives and derive optimal decision conclusions. The workflow of APMS consists of four stages: preparation, information, decision, and evaluation, ensuring the scientific and systematic of the decision-making process.

This study conducted field research and empirical analysis on a practical megaproject of a comprehensive transport hub to verify the effectiveness of APMS. The results show that, in terms of both short-distance and long-distance transportation modes, the decision-making results of APMS are largely consistent with the preliminary programming outcomes of the project. However, regarding transfer modes, the APMS decision-making results revealed certain discrepancies between the project's current status and the preliminary programming.

APMS addresses the shortcomings in decision accuracy and stakeholder participation and integration in the current field of architectural programming. It not only enhances stakeholder participation and interaction but also considers various opinions and interests comprehensively. Additionally, APMS has significant potential in optimizing project performance, accelerating project processes, and reducing resource waste.

To enhance the load capacity and dynamic characteristics of gas foil conical bearings (GFCBs), two kinds of microgrooves (sector and Fibonacci-like shape) are arranged on the top foil surface.

The Reynolds equation considering gas rarefaction effect is solved by the finite difference method, in which the 2D plate element stiffness model is used for the grooved top foil. The influence of groove on the static characteristics is studied, and the dynamic characteristics of novel bearing are obtained by the perturbation method.

The results show that the gas rarefaction effect on the load capacities is negligible, and the novel GFCB with microgrooved top foil has higher load capacities. Moreover, the deeper groove is conductive to the dynamic stability improvement. The positive Fibonacci-like groove seems to be the most suitable shape, which can largely increase the axial load capacity with little additional torque cost. And the improvement of dynamic characteristics for the Fibonacci-like grooved GFCB is also more favorable.

As the low cost of groove processing, it is an effective way to improve GFCB’s performance and even can be used to upgrade the bearings in service.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0148/