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This paper investigates individual investors' responses to stock underpricing and how their trading decisions are affected by analysts' forecasts and recommendations.

This empirical study uses mutual fund fire sales as an exogenous source that causes stock underpricing and analysts' forecasts and recommendations as price-correcting information. The study further uses regression analysis to examine individual investors' responses to fire sales and how their responses vary with price-correcting information.

The authors first show that individual investors respond to mutual fund fire sales by significantly decreasing net buys, and this effect appears to be prolonged. Next, the authors find that the decrease of net buys diminishes following analysts' price-correcting earnings forecast revisions and stock recommendation changes. Hence, the authors suggest that individual investors are not “wise” enough to recognize flow-driven underpricing; however, this response is weakened by analysts' price-correcting information.

There is an ongoing debate in the literature about whether individual investors should be portrayed as unsophisticated traders or informed traders who can predict future returns. The authors study a unique information event and provide new evidence related to both perspectives. Overall, our evidence suggests that the “unsophisticated traders” perspective is predominant, whereas a better information environment significantly reduces individual investors' information disadvantage. This finding could be of interest to both academic researchers and regulators.

Drawing on experiential learning theory, this study seeks to understand how the perceived cultural difference in a foreign country and learning flexibility, which enables more integrated experiential learning from international experience, influence expatriates’ cultural intelligence (CQ) and consequently their adjustment and job performance.

Survey data were collected from 169 expatriates in China. Polynomial regression analyses were employed to test curvilinear relationships between cultural difference and CQ and between learning flexibility and CQ. Mediation hypotheses were tested either by the MEDCURVE procedure if a curvilinear relationship was confirmed or by the Haye’s Process procedure if a curvilinear relationship was not confirmed and instead a linear relationship was confirmed.

The results demonstrated a positive relationship between cultural difference and CQ and an inverted U-shape relationship between learning flexibility and CQ. CQ mediated the relationship between cultural difference and expatriate adjustment and partially mediated the relationship between learning flexibility and expatriate adjustment. CQ positively influenced expatriates’ job performance via expatriate adjustment.

Our findings suggest that companies should not hesitate to send expatriates on assignments to culturally very different countries and focus more attention on the selection of expatriates. The findings of this study suggest firms should choose candidates who are moderate or high in learning flexibility and could engage in integrated learning and specialized learning in a more balanced manner.

This research is the first study that examines the influence of learning flexibility on CQ and expatriate effectiveness. It examines cultural difference through the lens of experiential learning theory and argues that cultural difference constitutes “stimuli” in the experiential learning environment for individual learning in an international context. The results advance our knowledge of the role of experiential learning in developing capable global managers.

This paper aims to synthesize benzothiazole-azo disperse dyes which can be applied not only for dyeing and alkaline reduction of polyester fabric in one bath, but also for dyeing and peroxide bleaching of cotton/polyester blend fabric in one bath.

The synthesized benzothiazole-azo disperse dyes were confirmed by proton nuclear magnetic resonance (1H-NMR) spectroscopy, mass spectroscopy (MS) and UV–visible spectrophotometry. The performance on resistance to alkaline treatment and peroxide bleaching was tested by measuring the color strength of polyester fabric dyed with the synthesized benzothiazole-azo disperse dyes under high-temperature and high-pressure conditions.

Increasing the electron-withdrawing ability of the substituents in the diazo component and the electron-donating ability of the substituents in the coupling component resulted in a significant bathochromic shift of the maximum absorption wavelength. Except that the disperse dyes synthesized from the coupling components containing the hydroxyethyl group were unstable in alkaline solution, all others exhibited high resistance to alkaline treatment and peroxide bleaching.

The synthesized benzothiazole-azo disperse dyes provide the opportunities to combine dyeing and alkaline reduction of polyester fabric into one bath, and combine dyeing and peroxide bleaching of cotton/polyester blend fabric into one bath.

The synthesized benzothiazole-azo disperse dyes help to establish short processes of polyester and polyester/cotton blend fabrics so as to reduce energy consumption and raise production efficiency.

Efficient traffic incident management is needed to alleviate the negative impact of traffic incidents. Accurate and reliable estimation of traffic incident duration is of great importance for traffic incident management. Previous studies have proposed models for traffic incident duration prediction; however, most of these studies focus on the total duration and could not update prediction results in real-time. From a traveler’s perspective, the relevant factor is the residual duration of the impact of the traffic incident. Besides, few (if any) studies have used dynamic traffic flow parameters in the prediction models. This paper aims to propose a framework to fill these gaps.

This paper proposes a framework based on the multi-layer perception (MLP) and long short-term memory (LSTM) model. The proposed methodology integrates traffic incident-related factors and real-time traffic flow parameters to predict the residual traffic incident duration. To validate the effectiveness of the framework, traffic incident data and traffic flow data from Shanghai Zhonghuan Expressway are used for modeling training and testing.

Results show that the model with 30-min time window and taking both traffic volume and speed as inputs performed best. The area under the curve values exceed 0.85 and the prediction accuracies exceed 0.75. These indicators demonstrated that the model is appropriate for this study context. The model provides new insights into traffic incident duration prediction.

The incident samples applied by this study might not be enough and the variables are not abundant. The number of injuries and casualties, more detailed description of the incident location and other variables are expected to be used to characterize the traffic incident comprehensively. The framework needs to be further validated through a sufficiently large number of variables and locations.

The framework can help reduce the impacts of incidents on the safety of efficiency of road traffic once implemented in intelligent transport system and traffic management systems in future practical applications.

This study uses two artificial neural network methods, MLP and LSTM, to establish a framework aiming at providing accurate and time-efficient information on traffic incident duration in the future for transportation operators and travelers. This study will contribute to the deployment of emergency management and urban traffic navigation planning.

The purpose of this paper is to develop the model of telemetry data processing flow (TDPF) for TDPF development and the TDPF run-time infrastructure to improve the spacecraft health monitoring capability.

This research tries to develop the TDPF by flow-based programming (FBP) method and the component-based telemetry data processing software.

The result from the case study is positive, thus reflecting the appropriateness of the suggested method.

Application of the proposed TDPF model and the component-based telemetry data processing software may result in improved development efficiency and less development costs.

This paper provides an effective way to develop TDPF without recompiling the software. It greatly facilitates the TDPF development that hopefully will save the TDPF development cost.