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Forecasting population movement trends is crucial for implementing effective policies to regulate labor force growth and understand demographic changes. Combining migration theory expertise and neural network technology can bring a fresh perspective to international migration forecasting research.

This study proposes a conditional generative adversarial neural network model incorporating the migration knowledge – conditional generative adversarial network (MK-CGAN). By using the migration knowledge to design the parameters, MK-CGAN can effectively address the limited data problem, thereby enhancing the accuracy of migration forecasts.

The model was tested by forecasting migration flows between different countries and had good generalizability and validity. The results are robust as the proposed solutions can achieve lesser mean absolute error, mean squared error, root mean square error, mean absolute percentage error and R² values, reaching 0.9855 compared to long short-term memory (LSTM), gated recurrent unit, generative adversarial network (GAN) and the traditional gravity model.

This study is significant because it demonstrates a highly effective technique for predicting international migration using conditional GANs. By incorporating migration knowledge into our models, we can achieve prediction accuracy, gaining valuable insights into the differences between various model characteristics. We used SHapley Additive exPlanations to enhance our understanding of these differences and provide clear and concise explanations for our model predictions. The results demonstrated the theoretical significance and practical value of the MK-CGAN model in predicting international migration.

This paper aims to investigate how online consumer reviews (OCRs), countdowns and self-control affect consumers' online impulse buying behavior in online group buying (OGB) and uncover the relationship between these factors.

Based on the stimulus-organism-response (SOR) framework, this research examines the effects of OCRs, countdowns and self-control on users' impulse purchases. First, the influence of emotions on impulse purchases in group purchasing is investigated. In addition, this study innovatively applies stress-coping theory to group buying research, with countdowns exerting temporal pressure on consumers and OCRs viewed as social pressure, to investigate in depth how countdowns and OCRs affect users' impulse purchase behavior. Finally, this study also surveys the moderating role of users' self-control in the impulse purchase process.

The results show that the perceived value of OCRs and positive emotions (PE) were positively correlated with impulsiveness (IMP) and the urge to buy impulsively (UBI), while negative emotions (NE) were negatively correlated with IMP. Countdowns (CD) had a positive effect on UBI. Self-control can indirectly affect users' impulse buying by negatively moderating the relationship between PE and UBI, PE and IMP and CD and UBI.

The research results can help group buying platforms and related participants understand the factors influencing users' impulse purchases in OGB and facilitate them to better design strategies to increase product sales.

Lean management has been used in various constructions around the world for more than a quarter of a century, and it is an important factor in the construction of new projects. In relation to demolition management, only standards and codes and general principles of demolition of specific buildings were evaluated. The purpose of this study is providing relation between lean management on demolition processes of municipality buildings evaluated.

This study investigates the lean demolition of demolished and renovated buildings in a metropolitan area that can be extended to all cities. In the first stage, the effective factors in the demolition of the building based on lean management were identified through a valid questionnaire based on the valid Delphi approach. Social, economic and environmental considerations were considered in designing the appropriate questionnaire.

The modified approach between the fuzzy method and partial least squares was used to evaluate important variables. All of the modified processes were developed in MATLAB by the authors of this paper. The results show that customer-focused degradation parameter has the weakest effect and waste removal variable has the most effect on lean management.

Statistical results show that there is no significant difference between the effect of lean management on variables such as demolition time, quality and type of construction (p < 0.05).

The purpose of this study is to assess the impact of Covid-19 on sustainable fashion consumption behavior by proposing a conceptual framework combining consumer-specific factors and product-specific factors with a special emphasis on consumer value perceptions.

Theory of consumption value was integrated into the knowledge, attitude behavior model in the conceptual framework having consumer-specific and product-specific aspects. Perceived value (PERVAL) scale was used to measure value perceptions. The model was verified by a survey conducted among a random sample of 520 participants. The factors were extracted by using exploratory factor analysis and then confirmed by using confirmatory factor analysis. The hypotheses in the conceptual model were tested for different consumer groups, and the strength of the relationships was calculated by using multigroup analysis in structural equation modeling.

It was observed the environmental concern raised the need for getting knowledge about the environment. The impact of environmental knowledge on the value perception of sustainable fashion products varied for the consumers affected by Covid-19 at different levels. Quality perception and price perception were influenced most by environmental knowledge in that order for the consumers with “high fear and uncertainty” and “low fear and uncertainty”. Similarly, the perceived emotional and social values were influential on purchase intention for consumers with high fear and uncertainty, whereas price and social value perceptions were influential for the consumers with low fear and uncertainty.

This study is the initial study that investigated the impact of the Covid-19 pandemic on the consumption of sustainable fashion products. The integration of theory of consumption value into the knowledge, attitude behavior model allowed identifying the relationship between environmental issues and sustainable fashion consumption. Using the PERVAL scale for measuring perceived value, the study provided valuable insights for understanding the most important value dimensions for sustainable fashion products for consumer groups affected by Covid-19 at different levels. The results regarding the changes in the rankings related to the impact of environmental knowledge on dimensions of perceived value and the impact of perceived values on purchase intention enabled the integrated model to explain the attitude–behavior gap.