The study focused on analyzing hospitality management and services and their effects on hotels and resorts' customer satisfaction. The hospitality management and good services are key to satisfying customers, especially in the tourism sector, in providing the necessary and desirable goods and services to travelers in the Nueva Ecija, Philippines, and worldwide. This analysis used the design of quantitative resaerch to secure a relevant answer to the study's problem. And in selecting the sample respondents, the researcher used a total sampling technique. A total of 75 respondents composing of 40 customers/travelers, 33 staff, and two owners/managers were selected as respondents. The findings shows that the majority of the respondents were satisfied with the owner/s responses on issues and concerns of their customers regarding the hotel services and management. The proposed research strategies to product diversification and event management, the destination's image, sustainable visitor management framework, marketing, branding strategies, collaborations, and cooperation among its stakeholders. The results show that the growth of the tourism industry can break down the based economic structure. Therefore, some strategic measures are required to achieve sustainable tourism in the province of Nueva Ecija

In this paper Artificial Neural Network are applied to serve as an Intelligent Traveling Agent. The proposed agent is used in the problem domain of' Air Line Travel'. Subsequently this software has been developed which will categorize the incoming emails in three sections. The software first retrieves. Emails sent by clients belonging to different natures. The software has been trained using Neural Network based learning algorithm using both on - line and off - line methods and characterization curve is proposed to obtained after training the designed Neural Network using MA TLAB software. We have also design an interface for this system using VB language. The proposed system differentiates emails into four categories. These are Reservation, Confirmation, Cancellation and Neutral. The scheme has been tested for 100 users with a success rate of 90% in normal case. The on line learning facilitates the Neural Network to recognize new words. The proposed agent is capable to satisfy its importance.