Predicting tourism loyalty using an integrated Bayesian network mechanism

An economic early warning approach based on Bayesian Networks mechanism?

“…A BN is a graphical model of variables and their relationships based on probability theory [13]. It is is a powerful tool for knowledge representation and reasoning under conditions of uncertainty (Cheng et al, 2002), and visually presents the probabilistic relationships among a set of variables.…”

A neural network approach to predicting price negotiation outcomes in business-to-business contexts

“…Neural networks have been applied to various studies in economics (Kaastra & Boyd, 1996), consumer choice (Chiang et al, 2006;Hu, Shanker, & Hung, 1999), and customer loyalty (Hsu, Shih, Huang, Lin, & Lin, 2009) and information systems adoptions (Chong, 2013). These studies showed that neural networks can be applied to broad areas of research, consistently providing good results.…”

Optimization of SARIMA model using genetic algorithm method in forecasting Singapore tourist arrivals to Malaysia

“…Statistical and mathematical models could provide substantial contributions to the understanding and prediction of tourist arrivals and their trends of growth each year. Statistical tools such as time series analyses [4], [5], have been used by several authors to describe and forecast the number of tourists visiting in any country. Among these models, the seasonal autoregressive integrated moving average (SARIMA) model is useful in situations when the time series data exhibit seasonality-periodic fluctuations that recur with about the same intensity each year.…”