This study examines the possibilities of enhancing relationship between external factors and five main steps of the customer journey influence on brand trust. Our aim is to fill a gap of empirical studies on the online channel in Thailand. We identify four external factors that contribute to each step of customer journey base on customer journey map theory. Data collected from 400 respondents was tested against the research model using a partial least squares (PLS) approach. Our hypotheses testing the determinants set of the customer journey with a statistical inferential analysis that, show the results support 7 of the 9 hypotheses, with a significant relationship between analysed constructs (Social influencer, eWom, and Marketing campaign) which are the factors that might contribute to online customer journey at the present.

The climate change which is essential for daily life and especially agriculture has been forecasted by global climate models (GCMs) in the past few years. Statistical downscaling method (SD) has been used to improve the GCMs and enables the projection of local climate. Many pieces of research have studied climate change in case of individually seasonal temperature and precipitation for simulation; however, regional difference has not been included in the calculation. In this research, four fundamental SDs, linear regression (LR), Gaussian process (GP), support vector machine (SVM) and deep learning (DL), are studied for daily maximum temperature (TMAX), daily minimum temperature (TMIN), and precipitation (PRCP) based on the statistical relationship between the larger-scale climate predictors and predictands in Thailand. Additionally, the data sets of climate variables from over 45 weather stations overall in Thailand are used to calculate in this calculation. The statistical analysis of two performance criteria (correlation and root mean square error (RMSE)) shows that the DL provides the best performance for simulation. The TMAX and TMIN were calculated and gave a similar trend for all models. PRCP results found that in the North and South are adequate and poor performance due to high and low precipitation, respectively. We illustrate that DL is one of the suitable models for the climate change problem.