The Relationship Between Awareness and Commitment to Participate in the Green Tourism Model of Local Communities: Evidence from the Hmong People Community in Lao Cai Province - Vietnam

Purpose: This study explores the impact of green tourism on the Hmong community in Lao Cai province, Vietnam, including their awareness of sustainable tourism principles and factors influencing their engagement. It aims to provide practical recommendations to enhance understanding and commitment to sustainable tourism, contributing to the existing knowledge and offering insights applicable to other regions and communities interested in promoting green tourism.   Theoretical framework:   The theoretical framework for this research draws upon concepts and theories from sustainable tourism, community development, and environmental psychology, explicitly focusing on community participation and empowerment in tourism development. It explores the impact of the Hmong people's awareness, involvement in decision-making, and sense of ownership over green tourism initiatives on their commitment to participate in the green tourism model.   Design/methodology/approach:   This study employed a mixed-methods approach, a quantitative survey, to collect data from 200 Hmong individuals in Lao Cai province in early 2022. A thorough literature review accompanied the survey design, distribution, collection, and analysis of responses. By utilizing this approach, the research aims to comprehensively understand the Hmong community's awareness and commitment to participating in the green tourism model in Lao Cai province, Vietnam.   Findings:  The study's findings show that green tourism's environmental and sociocultural benefits positively influence the Hmong community's awareness and commitment to sustainable tourism practices. However, economic benefits were not significantly associated with public perception, indicating a greater emphasis on cultural heritage conservation than financial gains. These results highlight the significance of involving local communities in decision-making and offering tangible benefits to foster their active engagement in sustainable tourism initiatives.   Research, Practical & Social implications: This study makes two significant contributions to the existing knowledge. Firstly, it provides a comprehensive understanding of the impact of green tourism on local communities, particularly the Hmong community in Vietnam. Secondly, it highlights the vital role of community participation in sustainable tourism development. The findings recommend policymakers' active involvement of local communities in decision-making and the provision of tangible benefits for their engagement in sustainable tourism practices, promoting their commitment to sustainable tourism.   Originality/value: Being the pioneering study on this subject in Vietnam, this research holds a unique significance in raising awareness and fostering commitment among the Hmong community regarding their participation in green tourism within Lao Cai province. Furthermore, the study's findings can serve as a valuable resource for shaping policies and programs that actively involve the Hmong community in green tourism, leading to mutual benefits for the community and the local region

The Factors Influence the Intention to Invest in Green Tourism in Vietnam: Evidence from Business Survey

Purpose:  This research aims to examine the factors that impact the intention of businesses to invest in green tourism in Vietnam. The findings of this research can potentially provide insights and guidance to businesses and policymakers in making informed decisions regarding sustainable tourism practices and investments in the sector.   Theoretical framework:  The theoretical framework for this research topic could draw upon several relevant concepts and theories from the fields of sustainable tourism, community development, and environmental psychology.   Design/methodology/approach:  The methodology and approach for this research involve conducting a quantitative survey among businesses operating in the tourism industry in Vietnam during the year 2022. This includes designing and distributing the survey, collecting and analyzing the responses, and conducting a review of relevant literature. By using this mixed-methods approach, the research can provide a comprehensive understanding of the factors that influence businesses' intention to invest in green tourism in Vietnam.   Findings:  The study examines the factors that influence investment intentions in green  The findings reveal that government policies and regulations, funding and financial resources, local community involvement, and tourist demand have a significant and positive influence on investment intentions in sustainable tourism. However, public awareness and education, as well as infrastructure and technology, do not demonstrate a statistically significant impact on investment intentions.   Research, Practical & Social implications: The results indicate that investment intentions in green tourism are affected by government policies and regulations, as well as the accessibility of funding and financial resources. Additionally, the engagement of local communities and catering to the needs of environmentally and socially conscious tourists are crucial factors. However, the study also reveals that public awareness and education, as well as infrastructure and technology, do not have a statistically significant effect on investment intentions. The findings underscore the necessity for additional research to investigate the influence of public awareness and education on investment intentions and to tackle the challenge of low public awareness.   Originality/value:   Being the first research on this topic conducted in Vietnam, this study holds a unique position in advancing the understanding of sustainable tourism practices in the country's tourism industry. Additionally, the findings of this research can aid in developing policies and programs that promote sustainable tourism practices, which can have benefits for both the local communities and the tourism industry

STUDIES OF THE BENTHIC MACROINVERTEBRATE FOR WATER QUALITY MONITORING IN CAN GIO-HCMC

Joint Research on Environmental Science and Technology for the Eart

Fuzzy-proportional-integral-derivative-based controller for object tracking in mobile robots

This paper aims at designing and implementing an intelligent controller for the orientation control of a two-wheeled mobile robot. The controller is designed in LabVIEW and based on analyzed image parameters from cameras. The image program calculates the distance and angle from the camera to the object. The fuzzy controller will get these parameters as crisp input data and send the calculated velocity as crisp output data to the right and left wheel motor for the robot tracking the target object. The results show that the controller gives a fast response and high reliability and quickly carries out data recovery from system faults. The system also works well in the uncertainties of process variables and without mathematical modeling

Approximation of mild solutions of the linear and nonlinear elliptic equations

In this paper, we investigate the Cauchy problem for both linear and semi-linear elliptic equations. In general, the equations have the form $$\frac{\partial^{2}}{\partial t^{2}}u\left(t\right)=\mathcal{A}u\left(t\right)+f\left(t,u\left(t\right)\right),\quad t\in\left[0,T\right],$$ where $\mathcal{A}$ is a positive-definite, self-adjoint operator with compact inverse. As we know, these problems are well-known to be ill-posed. On account of the orthonormal eigenbasis and the corresponding eigenvalues related to the operator, the method of separation of variables is used to show the solution in series representation. Thereby, we propose a modified method and show error estimations in many accepted cases. For illustration, two numerical examples, a modified Helmholtz equation and an elliptic sine-Gordon equation, are constructed to demonstrate the feasibility and efficiency of the proposed method.Comment: 29 pages, 16 figures, July 201

Stochastic control for optimal power flow in islanded microgrid

The problem of optimal power flow (OPF) in an islanded mircrogrid (MG) for hybrid power system is described. Clearly, it deals with a formulation of an analytical control model for OPF. The MG consists of wind turbine generator, photovoltaic generator, and diesel engine generator (DEG), and is in stochastic environment such as load change, wind power fluctuation, and sun irradiation power disturbance. In fact, the DEG fails and is repaired at random times so that the MG can significantly influence the power flow, and the power flow control faces the main difficulty that how to maintain the balance of power flow? The solution is that a DEG needs to be scheduled. The objective of the control problem is to find the DEG output power by minimizing the total cost of energy. Adopting the Rishel’s famework and using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation. Finally, numerical examples and sensitivity analyses are included to illustrate the importance and effectiveness of the proposed model

Optimal generation for wind-thermal power plant systems with multiple fuel sources

In this paper, the combined wind and thermal power plant systems are operated optimally to reduce the total fossil fuel cost (TFFC) of all thermal power plants and supply enough power energy to loads. The objective of reducing TFFC is implemented by using antlion algorithm (ALA), particle swarm optimization (PSO) and Cuckoo search algorithm (CSA). The best method is then determined based on the obtained TFFC from the three methods as dealing with two study cases. Two systems with eleven units including one wind power plant (WPP) and ten thermal power plants are optimally operated. The two systems have the same characteristic of MFSs but the valve loading effects (VLEs) on thermal power plants are only considered in the second system. The comparisons of TFFC from the two systems indicate that CSA is more powerful than ALA and PSO. Furthermore, CSA is also superior to the two methods in terms of faster search process. Consequently, CSA is a powerful method for the problem of optimal generation for wind-thermal power plant systems with consideration of MFSs from thermal power plants

Minimize electricity generation cost for large scale wind- thermal systems considering prohibited operating zone and power reserve constraints

Wind power plants (WPs) play a very important role in the power systems because thermal power plants (TPs) suffers from shortcomings of expensive cost and limited fossil fuels. As compared to other renewable energies, WPs are more effective because it can produce electricity all a day from the morning to the evening. Consequently, this paper integrates the optimal power generation of TPs and WPs to absolutely exploit the energy from WPs and reduce the total electricity generation cost of TPs. The target can be reached by employing a proposed method, called one evaluation-based cuckoo search algorithm (OEB-CSA), which is developed from cuckoo search algorithm (CSA). In addition, conventional particle swarm optimization (PSO) is also implemented for comparison. Two test systems with thirty TPs considering prohibited working zone and power reserve constraints are employed. The first system has one wind power plant (WP) while the second one has two WPs. The result comparisons indicate that OEB-CSA can be the best method for the combined systems with WPs and TPs