Purchase intention for second-hand luxury goods: An empirical study of Chinese consumers.

Second-hand luxury goods feature both characteristics of luxury products like perceived value including social, emotional, and quality value, and second-hand goods like price-performance ratio. Enlarging the second-hand luxury market is of significance to protect the environment and save rare and valuable natural resources, and thus investigating the determinants of purchase intention is meaningful. From the perspective of the psychology of consumers, the influence of factors related to consumers (recycling awareness, subjective norms, attitudes, perceived behavioral control) and products (perceived value, price-performance ratio) on the intention to buy second-hand luxury goods is explored in this study through an online survey with Chinese consumers as a sample. The results are analyzed using the structural equation model (SEM) and show that consumers' attitudes, perceived behavioral control, and recycling awareness will promote the intention of purchasing second-hand luxury goods, and the perceived value and price-performance ratio of second-hand luxury goods also have a positive impact on the purchase intention. However, there is no significant relationship between subjective norms and purchase intention. In addition, this study also explores the interrelationship between constructs and draws corresponding conclusions, providing references for the subsequent development of the second-hand luxury market.

Prediction of driving stress on high-altitude expressway using driving environment features: A naturalistic driving study in Tibet.

OBJECTIVE: Owing to the harsh environment in high-altitude areas, drivers experience significant driving stress. Compared with urban roads or expressways in low-altitude areas, the driving environment in high-altitude areas has distinct features, including mountainous environments and a higher proportion of trucks and buses. This study aims to investigate the feasibility of predicting stress levels through elements in the driving environment. METHODS: Naturalistic driving tests were conducted on an expressway in Tibet. Driving stress was assessed using heart rate variability (HRV)-based indicators and classified using K-means clustering. A DeepLabv3 model was built to conduct semantic segmentation and extract environment elements from the driving scenarios recorded through a camera next to the driver's eyes. A decision tree and 4 other ensemble learning models based on decision trees were built to predict driving stress levels using the environment elements. RESULTS: Fifty-six indicators were extracted from the driving environment. Results of the prediction models demonstrate that extreme gradient boosting has the best overall performance with the F1 score (harmonic mean of the precision and recall) and G-mean (geometric mean of sensitivity and specificity) reaching 0.855 and 0.890, respectively. Indicators based on the variation rate of trucks and buses have high feature importance and exhibit positive effects on driving stress. Indicators reflecting the proportion of mountain, road, and sky features negatively affect the expected levels of driving stress. Additionally, the mountain feature demonstrates multidimensional effects, because driving stress is positively affected by indicators of the variation rate for mountain elements. CONCLUSIONS: This study validates the prediction of driving stress using environment elements in the driver's field of view and extends its application to high-altitude expressways with distinct environmental characteristics. This method provides a real-time, less intrusive, and safer method of driving stress assessment and prediction and also enhances the understanding of the environmental determinants of driving stress. The results hold promising applications, including the development of a driving state assessment and warning module as well as the identification of high-risk road sections and implementation of control measures.

[Photophysical properties of novel organic europium (III) complexes].

Based on fluorescence and absorbance spectroscopy, the photophysical properties and mechanisms of novel organic europium (III) complexes in the case of different concentration in ethanol solution and solid flour were studied at room temperature. It was found that the complex absorption spectra are mainly due to the Phenanthroline ligand, gradually exhibit saturated absorption from shortwave to long wave with the concentration increased, and stretch and broaden to long wave. And four characteristic peaks of the fluorescence spectra are all emission spectra of Eu3+ in the complex, and the strongest emission wavelength was 617 nm corresponding to the (5)D0-->(7)F2 transition of Eu2+. And then, it is presented that the perturbation of acetanil ligand changes the parity state of Eu3+ energy field, resulting in the increase of (5)D0-->(7)F2 transition probability, making phenanthroline transfer its energy absorbed to Eu3+, and inducing 617nm strong emission of fluorescence peak.