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This paper aims to explore the effectiveness of 360-degree virtual reality (VR) videos compared to traditional preview modes in shaping customer perceptions and behavioral intentions toward the hospitality service provider. Specifically, the study investigates how self-construal moderates this relationship, offering novel and nuanced understanding of the customer decision-making process in the hospitality sector.

Three experiments were carried out. Study 1 examined the impact of preview modes on customers’ behavioral intentions. Study 2 examined the psychological mechanism of mental imagery and being hooked in the relationship between preview modes and behavioral intentions. Study 3 examined the moderating role of self-construal in the relationship between preview modes and behavioral intentions.

The study findings revealed that 360-degree VR videos are more effective than traditional preview modes in determining customers’ behavioral intentions. Mental imagery and being hooked explain this relationship. Furthermore, customers with highly independent self-construal evaluate 360-degree VR videos more favorably, while those with highly interdependent self-construal evaluate traditional preview modes more positively.

The research indicates that adopting VR applications can offer competitive advantage for hospitality service providers. The study findings provide hospitality providers with insights to tailor their marketing strategies by selecting preview modes that align with the psychological profiles of the customers.

The originality of the study lies in its pioneering efforts to explore how self-construal shapes customer responses to different preview modes. Furthermore, this study reveals the importance of psychological constructs in understanding the impact of VR applications on customer behaviors.

This paper aims to enhance the machining accuracy of hybrid robots by treating the moving platform as the first joint of a serial robot for direct position measurement and integrating external grating sensors with motor encoders for real-time error compensation.

Initially, a spherical coordinate system is established using one linear and two circular grating sensors. This system enables direct acquisition of the moving platform’s position in the hybrid robot. Subsequently, during the coarse interpolation stage, the motor command for the next interpolation point is dynamically updated using error data from external grating sensors and motor encoders. Finally, fuzzy proportional integral derivative (PID) control is applied to maintain robot stability post-compensation.

Experiments were conducted on the TriMule-600 hybrid robot. The results indicate that the following errors of the five grating sensors are reduced by 94%, 93%, 80%, 75% and 88% respectively, after compensation. Using the fourth drive joint as an example, it was verified that fuzzy adaptive PID control performs better than traditional PID control.

The proposed online error compensation strategy significantly enhances the positional accuracy of the robot end, thereby improving the actual processing quality of the workpiece.

This method presents a technique for achieving online error compensation in hybrid robots, which promotes the advancement of the manufacturing industry.

This paper proposes a cost-effective and practical method for online error compensation in hybrid robots using grating sensors, which contributes to the advancement of hybrid robot technology.

The Public–Private Partnership (PPP) modality plays an important role in the procurement of global infrastructure projects. Regarding PPP's complex transaction structure, pricing of a PPP project is critical to both parties where the government pursues a high value for money (VFM) and the investor strives to maximize its financial gains. Despite the straightforward win–win principle, a formidable compromise is often the case to end up with a fairly acceptable price, subject to many determinants such as the risk profile, expected return, technological innovation and capacities of both parties. Among them, this study chooses to examine the “managing flexibility” (MF) capacity of investors in pricing of a PPP project, in light of the widely recognized importance of a real-option perspective toward the long term, complex and uncertain PPP arrangement. This study addresses two major questions: (1) how is MF in PPP projects to be valued and (2) how are PPP projects to be priced when considering a project's MF value.

A binomial tree model is used to evaluate the MF value in PPP projects. Based on the developed MF pricing model, net present value (NPV) and adjusted VFM value are then calculated. Finally, a multi-objective decision-making method (MODM) was adopted to determine the optimal level of returns based on invested capital (ROIC), return on operation maintenance (ROOM) and concession period.

The applicability and functionality of the proposed model is investigated using a real project case. For a given return, extended NPV and adjusted VFM value were calculated and analyzed using sensitivity analysis. Factor influence is shown by the model to be dependent on factor impact on cash flow. Subsequently, a multi-objective decision-making (MODM) model was adopted to determine the optimal level of returns, where the solution approximates the real-world bidding price. Results confirm that the pricing model provides a reliable and practical PPP proposal pricing tool.

This study proposes an integrated framework for valuing MF in PPP projects and thus more accurately determine optimal pricing of PPP projects than revealed in extant research. The model offers a practical tool to aid in the valuation of PPP projects.