Data Analytics-Based Algorithm for Returning Intention to Rural Tourism Destinations of Tourists

The paper seeks to evaluate the decision criteria in the returning intention to rural tourism destinations of tourists in Vietnam. This research sample comprises tourists. This chapter used the quantitative technique of PLS-SEM. The PLS Algorithm shows that the empirical model has a measurement of determination of 0.876, with 87.6% variation of intention, perceived value, attitude, travel motivation, subjective norm, and perceived behavior control. The factor that has the strongest influence on the intention to return to a rural tourist destination (INT) is the perceived value (PV) of tourists (0.367), followed by the second strongest factor on the returning intention to rural tourism destinations is the subjective norm factor (SN) of tourists (0.340). Finally, managers need suggestions to raise the returning intention to rural tourism destinations of tourists: evidence from Vietnam.