This research investigates the relationship between the quality of airline services, customer satisfaction, and brand loyalty with low-cost airlines in Bangkok’s aviation business. It uses structural equation modeling (SEM) to examine the replies of 521 passengers. The study demonstrates a robust and favorable correlation between the quality of service and customer satisfaction, with a direct impact coefficient of 0.961. Furthermore, service quality directly (0.708) and indirectly (0.284) impact brand loyalty. These impacts are mediated by customer satisfaction, which directly affects brand loyalty with a correlation of 0.296. The model explains 92.3% and 99.0% of the variation in customer satisfaction and brand loyalty, respectively, suggesting a robust and reliable match. The demographic study reveals that the predominant group of participants consists of well-educated, middle-income women who regularly use airline services. These results highlight the importance of service quality in improving customer satisfaction and promoting brand loyalty among travelers. Airlines should emphasize the ongoing enhancement of service quality and customer satisfaction to sustain their competitive edge. This research enhances the existing body of knowledge by emphasizing the intermediate function of customer satisfaction and presenting detailed observations relevant to Bangkok’s aviation industry, providing guidance for infrastructural development and investment. It also offers practical suggestions for managing service quality and implementing customer retention strategies.

In the process of forest recreation value development, there are some characteristics, such as large amount of investment capital, long financing recovery cycle and high potential risks, which lead to limited capital source and prominent financing risks. To achieve sustainable development, forest recreational value development enterprises must solve the financing dilemma, therefore, it is very urgent to identify the financing risk factors. The research constructed financing risk evaluation index system through WSR (Wuli-Shili-Renli) methodology (from affair law, matter principle and human art dimensions), taking S National Forest Park at Fujian Province as a case study, the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method were used for empirical analysis. The results showed that for the first level indicators, operational risk should be paid close attention to, followed by political risk and environmental risk. Among the secondary level indicators, policy changes, financing availability and market demand need attention, which are consistent with the result of field survey. Based on that, countermeasures were put forward such as the multiple collaborative linkage and effective internal control; reduction on operating costs and broaden financing channels; encouragement diversification of investment entities and improvement of financial and credit support; strengthening government credit supervision, optimizing financing risk evaluation, and building a smart tourism financing information platform, to reduce and control financing risks, then promote the development of forest recreation value projects.

The dairy industry is considered one of the most needed industries in almost every country; this is due to the continuous daily demand of its different products. Nevertheless, this industry consumes large amount of water, energy and material resources, and generates large quantities of liquid and solid wastes. In the sequel, under the pressure of fulfilling the 17 sustainable development goals (17 SDGs), it is important to address the sustainability of this sector in the world and particularly in developing countries. This study aims at assessing the impact of environmental, economic and social sustainability practices on the organizational performance of dairy industry in Palestine. To this end, a quantitative-research approach, based on a questionnaire for data collection, was adopted. Data has been collected from a convenient sample of 15 dairy factories working in West Bank in Palestine during a three-month period from March to May, 2023. Inferential statistical analyses were conducted as well. The results revealed that there is a difference between the median values of environmental and economic practices. In addition, the results showed that there is a medium relationship between sustainability practices and organizational performance. However, the economic practices proved to have the strongest impact then social practices; while, there is no impact of environmental practices on organizational performance. Furthermore, the results showed that this industry consumes larger amount of water as well as it generates large amounts of wastewater that mainly discharged to the drainage system without treatment for recycling or reuse. Several sound recommendations are given at the end of this paper. It worth mentioning that there are no previous studies conducted on the dairy industry sector in Palestine about sustainability assessment.

Urbanization and suburbanization have led to high population growth in certain city regions, resulting in increased population density and mobility. Therefore, there is a need for a concept to address congestion, public transportation, information and communication systems, and non-motorized vehicles. Smart mobility is a concept of urban development as part of the smart city concept based on information and communication technology. Through this concept, it is expected that transportation services will be easily accessible, safe, comfortable, fast, and affordable for the community. This research aims to analyze smart mobility and its relationship with regional transportation planning and the development of South Tangerang, as well as to design a policy strategy model for the planning and development of South Tangerang with smart mobility. The research method used in this study is a mixed method, including analyzing the relationships and weighting of relationships between variables using the Cross Impact Multiplication applied to a classification (MICMAC) matrix. Multi-criteria decision analysis (MCDA) with Promethee software is also used to obtain the necessary policies. The results of this research indicate that the measurement of relationships between variables shows that smart mobility influences regional transportation planning, smart mobility affects regional development, and regional planning affects regional development. This research also provides alternative policies that policymakers should implement in a specific order. First, ensure the availability of public transportation; second, improve public transportation safety; third, enhance public transportation security; fourth, improve public transportation routes; fifth, provide real-time information access; sixth, improve transportation schedules; and seventh, increase the number of bicycle lanes.

The purpose of this study was to examine the effect of E-integrated marketing communication on consumers’ purchasing behavior of mobile services. The population for the study involves all orange telecom mobile service customers in Jordan. Three hundred ninety-five questionnaires were distributed to orange telecom customers in Jordan, however, 375 only returned, which has been used for analysis. structural equation modeling using programs such as AMOS was used to investigate the impact of E-integrated marketing communication on consumers’ purchasing behavior. Data was collected through questionnaires was sent to study sample. The results of the study showed that E-integrated marketing communication had a positive impact on consumers’ purchasing behavior. Based on the findings, the study recommended that Orange Telecom should focus more on e-public relations to create a favorable image of the company among different groups of consumers, which can potentially enhance their purchasing behavior towards its mobile services. It is imperative for Orange Telecom to prioritize its e-integrated marketing communication strategy to effectively reach out to its target audience and influence their purchase decisions.

Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Autoencoder (VAE), and results were compared to select the optimal model in terms of performance and forecasting accuracy. The difference of actual and predicted demand values also ascertain LSTM’s ability to identify latent features and basic trends in the data. Further, some of the research works were focused on computational efficiency and scalability of the proposed methods for providing the guidelines to the companies for the implementation of the complicated techniques in demand forecasting. Based on these results, LSTM networks have a promising application in enhancing the demand forecasting and consequently helpful for the decision-making process regarding inventory control and other resource allocation.