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This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.

In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.

Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.

This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.

The understanding of how to mitigate opportunism in construction projects is still limited and conflicting. The complexity of causalities and interdependence among antecedents of opportunism (transaction characteristics and governance mechanisms) is the major obstacle to current research. This study takes a holistic perspective to explore the different combinations of conditions that lead to high opportunism and low opportunism in project management.

Through 2 phases of the interview and questionnaire survey, the 91 valid survey data were collected from the buyer–seller relationships in construction projects and analyzed by adopting fuzzy-set qualitative comparative analysis.

A single transaction characteristic is rarely sufficient to explain opportunism, and combinations of different transaction characteristics and governance mechanisms (performance ambiguity, asset specificity, buyer's requirement certainty, informal control, and formal control) have different effects on opportunism. In the case of extremely unsatisfactory transaction characteristics, even the combination of formal and informal control cannot prevent high opportunism. The combination including low-formal control and high-asset specificity easily leads to high opportunism. Besides, performance ambiguity is a vital factor in mitigating high opportunism or achieving low opportunism.

Previous studies have always addressed the role of one or some factors independently and separately. This study is one of the first to explore the different combinations of conditions that result in high opportunism and low opportunism in project management based on transaction costs economics and agency theory.

This study aims to explore the relationships between consumer data vulnerability, peer privacy concerns and consumers' continued usage intention of sharing accommodation platforms, as well as the moderating effects of the various benefits perceived by consumers.

Data were collected from 327 consumers of sharing accommodation platforms in China. Partial least squares (PLS)-structural equation modeling (SEM) was conducted to test the research hypotheses.

The results suggest that both consumer data vulnerability and peer privacy concerns have negative effects on consumer's continued usage intention of sharing accommodation platforms, which can be further mitigated by consumer perceived economic, social and emotional benefits. This study also finds that consumer data vulnerability has a positive effect on consumer's peer privacy concerns.

This study gives that managers of sharing accommodation platforms a better understanding of how consumers respond to their data vulnerability on sharing accommodation platforms. In addition, this study also highlights the measures that platforms may employ to mitigate the negative influence of consumer data vulnerability and consumers' peer privacy concerns, as well as the measures to reduce consumers' peer privacy concerns.

While previous studies mainly examined the driving forces of consumers' engagement in sharing accommodation, this study focuses on the impediment. With communication privacy management theory to explore the relationships between consumer data vulnerability, peer privacy concerns and continued usage intention of sharing accommodation platforms, as well as the moderating effects of consumers' perceived benefits, this study facilitates a more comprehensive understanding of consumers' engagement in sharing accommodation.

Fused deposition modeling (FDM) is an extensively used additive manufacturing method with the capacity to build complex functional components. Due to the machinery and environmental factors during manufacturing, the FDM parts inevitably demonstrated uncertainty in properties and performance. This study aims to identify the stochastic constitutive behaviors of FDM-fabricated polylactic acid (PLA) tensile specimens induced by the manufacturing process.

By conducting the tensile test, the effects of the printing machine selection and three major manufacturing parameters (i.e., printing speed S, nozzle temperature T and layer thickness t) on the stochastic constitutive behaviors were investigated. The influence of the loading rate was also explained. In addition, the data-driven models were established to quantify and optimize the uncertain mechanical behaviors of FDM-based tensile specimens under various printing parameters.

As indicated by the results, the uncertain behaviors of the stiffness and strength of the PLA tensile specimens were dominated by the printing speed and nozzle temperature, respectively. The manufacturing-induced stochastic constitutive behaviors could be accurately captured by the developed data-driven model with the R² over 0.98 on the testing dataset. The optimal parameters obtained from the data-driven framework were T = 231.3595 °C, S = 40.3179 mm/min and t = 0.2343 mm, which were in good agreement with the experiments.

The developed data-driven models can also be integrated into the design and characterization of parts fabricated by extrusion and other additive manufacturing technologies.

Stochastic behaviors of additively manufactured products were revealed by considering extensive manufacturing factors. The data-driven models were proposed to facilitate the description and optimization of the FDM products and control their quality.

Leveraging the technology acceptance model (TAM) and the stimulus–organism–response (S–O–R) theory, this paper aims to investigate how the utilitarian and hedonic factors in virtual reality (VR) technologies affect consumers' intention to travel in the endemic phase of COVID-19. At the same time, the study incorporated emotional engagement and two forms of trust as possible organisms for this model.

Through snowball sampling, data collected from 263 respondents were analysed using the partial least square structural equation modelling (PLS-SEM).

The findings revealed that among the different forms of hedonic and utilitarian factors, all but perceived entertainment has a significant positive relationship to emotional engagement. Additionally, emotional engagement positively influences trust in the product and seller. However, the results show that only trust in the seller has a significant relationship with travelling intention. Predictive analysis shows that the model displays a strong predictive power.

This study differentiates from the existing literature by investigating the effect of VR technologies on the two different forms of trust and emotional engagement on travelling intention. This study extends earlier studies by supplementing the explanatory perspective with a predictive focus, which is particularly important in making sound recommendations on managerial decision-making.

Fun at workplace is considered an important initiative to build co-working communities, and this study aims to study its role in promoting the innovative behaviour of co-workers [members of co-working spaces (CWS)] and the mechanism of its influence.

Based on the theory of social exchange and resource conservation, the authors conducted a qualitative study to explore the four dimensions of workplace fun and a quantitative study to empirically analyse the relationship between community embeddedness, organisational embeddedness, workplace fun and creativity of co-workers, taking K-space as an example.

Workplace fun is positively correlated with co-workers' creativity. Community embeddedness plays a complete mediating role between workplace fun and organisational embeddedness. Community embeddedness and organisational embeddedness play a chain-mediating role between workplace fun and creativity.

This study explores the process and impact of fun on employee creativity in a shared office environment by clarifying the composition of fun in CWS workplaces and the transmission mechanism of fun through informal community embeddedness and formal organisational embeddedness, expanding the research perspective on the factors influencing employee creativity in the new office model and enriching the research findings on the impact of fun at work on job performance.