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Few studies have examined technology-enhanced atmospheres for strengthening customer experience and brand engagement in physical store settings. This study builds on the social presence theory to test for the first time the moderating effects of virtual social presence on customer responses, through AR adoption in-store. Our study aims to understand the impact of technology-enhanced in-store atmospherics (TEISAs) with emphasis on AR elements and virtual social presence on customer experience and engagement behaviours (CEBs) in luxury settings.

Hypotheses are developed and a survey using 566 responses were collected using Qualtrics. T-tests, two-way ANOVA and structural equation modelling were used for analysis of CEBs. Moreover, using PLS-SEM, we test whether virtual social presence moderates this relationship in a cross-country context; Britain and China, two of the largest economies for luxury growth.

The findings demonstrate that TEISAs have a positive impact on emotion and perceived value, with virtual social presence moderating this relationship. The cross-cultural comparison results show that the impact of TEISAs on emotion and perceived value is stronger for British than for Chinese millennials.

Our model is the first to incorporate technology into various store atmospherics, to employ virtual social presence as a new moderator, and to provide empirical evidence on the effects of AR on customer experience and CEBs in the real-time luxury retail environment. This study is also the first to consider virtual social presence on social media as a moderating variable.

The wetting performance and intermetallic formation of a Sn/Ag/Cu alloy on printed circuit board (PCB) surfaces and on component terminations were studied in this work. Two different PCB surface finishes, immersion gold over electroless nickel (Ni/Au) and an organic solderability preservative (OSP), were studied. Chip components with Sn/Pb coating and a gull‐wing type component with 100% Sn coating were used in these experiments. Different reflow profiles were tested, and the dependence of the wetting performance, intermetallic layer thickness and the microstructure of the solder joints on the reflow profile were investigated.It was found that reflow process conditions did not significantly influence the spreading or intermetallic formation on either of the surfaces. Neither the wetting onto the component nor the general microstructure of the solder joints varied significantly with the reflow profile. When a Sn/Pb ‐coated component was used, the content and size of Pb‐rich phases in the solder joint increased with a longer time above liquidus or a higher reflow peak temperature.

Physics-informed neural networks (PINNs) have become a new tendency in flow simulation, because of their self-advantage of integrating both physical and monitored information of fields in solving the Navier–Stokes equation and its variants. In view of the strengths of PINN, this study aims to investigate the impact of spatially embedded data distribution on the flow field results around the train in the crosswind environment reconstructed by PINN.

PINN can integrate data residuals with physical residuals into the loss function to train its parameters, allowing it to approximate the solution of the governing equations. In addition, with the aid of labelled training data, PINN can also incorporate the real site information of the flow field in model training. In light of this, the PINN model is adopted to reconstruct a two-dimensional time-averaged flow field around a train under crosswinds in the spatial domain with the aid of sparse flow field data, and the prediction results are compared with the reference results obtained from numerical modelling.

The prediction results from PINN results demonstrated a low discrepancy with those obtained from numerical simulations. The results of this study indicate that a threshold of the spatial embedded data density exists, in both the near wall and far wall areas on the train’s leeward side, as well as the near train surface area. In other words, a negative effect on the PINN reconstruction accuracy will emerge if the spatial embedded data density exceeds or slips below the threshold. Also, the optimum arrangement of the spatial embedded data in reconstructing the flow field of the train in crosswinds is obtained in this work.

In this work, a strategy of reconstructing the time-averaged flow field of the train under crosswind conditions is proposed based on the physics-informed data-driven method, which enhances the scope of neural network applications. In addition, for the flow field reconstruction, the effect of spatial embedded data arrangement in PINN is compared to improve its accuracy.

Today’s business environment has the nature that challenges the decision-making processes of businesses with its many different factors including technological developments and changing consumer structures. Previous research focused on specific contexts of the business environment regarding marketing and innovation issues, however, an integrative approach can be helpful for understanding and taking actions. This study aims to present a comprehensive framework which employs sensemaking from management literature as an approach to evaluate the market environment. Following a conceptual approach for the methodology, a framework consisting of three stages: discovery, sensemaking, and prediction is included in the study. Proposed framework identifies the stages for the sensemaking of consumers and can guide marketing decision-makers for competitiveness in the digital world.

This study aims to investigate the effect of supply chain quality management on operational performance in Vietnamese manufacturing companies.

Questionnaire survey is conducted to collect data from Vietnamese manufacturing companies in the electronic/electric industry. Collected data were analyzed by using correlation analysis and hierarchical regression analysis.

This study points out the current situation of implementing supply chain quality management practices in Vietnamese manufacturing companies which are more focused on internal quality management practices than upstream and downstream quality management practices. Correlation and regression analyses that demonstrate the significant linkage between supply chain quality management practices and operational performance are confirmed in this study. Upstream and downstream quality management are found to be the significant predictor for high performance on quality, cost and delivery.

This study has some limitations that can be addressed in future studies. The first limitation is the relatively small sample size due to lack of time and resources. These constraint can be overcome in future works by collecting more data in diverse countries and industries to re-examine the framework. Furthermore, larger sample will allow researchers to apply other statistical methods such as path analysis and structural equation modelling, which would provide interesting results. Another limitation is that the collected data in this paper mainly rely on perceptions of the respondents, which may cause individual bias in analysis. To reduce this type of bias, both subjective and objective measurement of scales, especially performance measures, can be used in future studies.

This study provides empirical evidences that practitioners can use to improve a specific type of performance, especially in the context of emerging economies. In a turbulent and unpredictable business environment, it is emphasized that quality management should be extended at supply chain level to utilize the capabilities of external partners. In Vietnamese manufacturing firms, implementation of such practices as information technology links, information sharing, supplier involvement and customer involvement would lead to high level of operational performance.

Supply chain management and quality management are two fields of study that have gained much attention of researchers. However, the concept of supply chain quality management as well as its impact on business performance have not been fully studied, especially in context of a developing country. Through extensive literature review, this study proposes and tests an analytical framework that characterizes supply chain quality management into three elements: internal quality management, upstream quality management and downstream quality management. Subsequently, their impact on quality, cost and delivery are analyzed to provide better understanding of supply chain quality management in Vietnamese context.

The purpose of this paper was to present the process of building hardware and software for a collision avoidance system of a quadrotor capable of an indoor autonomous flight.

The system development was carried out in two steps. First, the quadrotor system was designed to mount mission equipments for an indoor flight. The prediction error minimization (PEM) method was used for system identification of the quadrotor, and the linear quadratic regulator (LQR) control method was used for the attitude control. Second, a collision detection system was realized by using a Kinect sensor, an embedded board and a ground control system (GCS). A Kinect sensor with embedded board can send the 3D depth information to GCS and then the GCS displays the 3D depth information with a warning message.

As the controller design requires a linear model, the PEM method was used in system identification. The LQR was used in controller design. It was found that the use of the PEM method for system identification was effective for developing a linear model required for a practical control system using LQR. As 3D depth information from a Kinect sensor is quite accurate in an indoor environment, a collision detection system with Kinect was successfully developed.

The step-by-step approach presented in this paper can be used to develop an autonomous aerial vehicle capable of navigating in an indoor environment with obstacles.

The primary contribution of the paper is the presentation of a practical method for developing a low-cost collision avoidance system for a quadrotor vehicle.

This paper aims to identify the optimal forming angle for the selective laser melting (SLM) process and evaluate the mechanical properties of the SLM-formed GH3536 alloy in the aero-engine field.

Forming the samples with optimized parameters and analyzing the microstructure and properties of the block samples in different forming angles with scanning electron microscope, XRD, etc. so as to analyze and reveal the laws and mechanism of the block samples in different forming angles by SLM.

There are few cracks on the construction surface of SLM formed samples, and the microstructure shows columnar subgrains and cellular subgrains. The segregation of metal elements was not observed in the microstructure. The pattern shows strong texture strength on the (111) crystal plane. In the sample, the tensile strength of 60° sample is the highest, the plasticity of 90° forming sample is the best, the comprehensive property of 45° sample is the best and the fracture mode is plastic fracture. The comprehensive performance of the part is the best under the forming angle of 45°. To ensure the part size, performance and support structure processing, additional dimensions are added to the part structure.

In this paper, how to make samples with different forming angles is described. Combined with the standard of forged GH3536 alloy, the microstructure and properties of the samples are analyzed, and the optimal forming angle is obtained.

The purpose of this study is to explore the ways in which work practices promote work-life balance when family time is available (as a spillover effect from work to personal life) and how differently they affect men and women.

A quantitative and longitudinal approach is taken based on data from a large database made up of 71,758 workers from 36 European countries, collected in 2021 by the European Working Conditions Survey. After preliminary analysis (including exploratory and confirmatory factorial analysis), the partial least square method was used to test the hypothesis of the conceptual model.

The results of this study reveal that some work practices (autonomy and confidence at work) positively affect work-life balance. The time available for family and domestic care positively affects work-life balance, and this effect is more relevant for women than for men.

These results are important for organizations that wish to promote not only family-friendly work practices but also above all gender-friendly work practices.

Based on a large sample of European workers, this study makes an important contribution by filling the gap on the understanding and importance of mechanisms outside the organizational context for promoting work-life balance through work practices, thus extending the notion of spillover effects while considering gender differences.

This research was to understand people's perceptions and trends in wearable robots and the research questions were as follows: (1) investigating key terms related to wearable robots that were frequently used by and exposed to people and (2) analyzing relationships among those key terms.

Textom, a big data collection and analysis software system, was used to collect data using the keyword – wearable robot.

The frequency-inverse document frequency, term frequency and central analyses were investigated, and the major key terms related to wearable robots and their connectivity were identified. After performing network analysis and convergence of iterated correlations analyses using UCINET and NetDraw programs, the major key term categories were identified.

It is important to understand how people think and perceive about wearable robots before developing wearable robots. The results of the research are expected to be helpful to better understand how people perceive and what key terms are mainly discussed by people in both countries and ultimately help when developing wearable robots with better market targeting approach methods.

Blockchain is widely applied in e-voting, shared economy areas and other government functioning. Fragmented findings and distributed literature need consolidation for a holistic view of the research domain. The purpose of this study is to comprehensively reviews the blockchain applications for government organizations and presents the past, present and future trends of blockchain applications for government organizations.

Systematic review protocol instrumentalized the systematic review of research articles published from 2013 to 2021. Science mapping discerns scientific actors’ trends and performance analysis like most influential authors, documents and sources. Content analysis of selected data set unfolds the past, present and future of blockchain applications for government organizations.

Blockchain technology offers enormous potential for the transformation of government organizations and public services. The primary areas are cryptocurrency, e-voting, shared economy, smart contracts, financial and health services, tourism, logistics and water sustainability.

This study reviewed only published research in journals and conference proceedings and excluded book reviews, book chapters and editorials from the review set. This study persuades governments and policymakers to invest in blockchain technology for transforming government organizations and public services.

This study highlights the importance of blockchain in government-controlled public departments, enhancing transparency and efficiency in public life.

Blockchain technology enhances transparency, traceability and accountability of public records.

This study pioneers in chronologically highlighting the importance of blockchain in government-controlled public departments.