The virtual reality (VR) applications in entertainment and tourism industry have become growingly intense among generation Z. Interestingly, some pilot research on tourism studied concluded the positive impact of its flow experience on adoption of VR tourism, which is also driving the risk of immersive addictive. In the context of tourism and information and communication technology (ICT)-based innovation, there is a lack of immersive addictive behavior (IAB)-related literature. In addition, during the currently ongoing pandemic crisis, VR technology has gained particular importance in the tourism industry among generation Z. The present venture underlines the mechanism of IAB, investigates the VR addiction while underlining the cognitive abilities of individuals. This study applies empirical framework of cognitive–behavioral model. Results demonstrate that in the case of VR tourism, the immersive experience (presence and flow) determines the addictive behavior. Furthermore, VR imagery (VI), psychological curiosity (PC), and VR convenience (VRC) have significant influence on the VR presence and immersive flow. Moreover, the practical and theoretical implications have been discussed in the current research to prevent IAB.
In modeling and designing micro combined heat and power cycle most important point is recognition of how the cycle operates based on the first and second laws of thermodynamics simultaneously. Analyzing data obtained from thermodynamic analysis employed to optimize MCHP cycle. The data obtained from prime mover optimization has been used for basic stimulus cycle. Assumptions considered for prime mover optimization has been improved, for example in making optimum operation condition by using genetic algorithms constant pressure combustion chamber was considered. The exact value of downstream and upstream pressure changes in the combustion chamber reaction has been obtained. After extraction of the appropriate relationship for the primary stimulus cycle, data required for the overall cycle analysis identified, By using these data optimum total cycle efficiency and constructing the first and second laws of thermodynamics has been calculated for it. After reviewing Thermodynamic governing relations in each cycle and using the optimum values that the prime mover has been optimized with, other cycles have been optimized. In best performance condition of cycle, electrical efficiency was 41 percent and the overall efficiency of the cycle was 88 percent, respectively. After using the second law of thermodynamics mathematical model Second law of thermodynamics efficiency and entropy production rate was estimated. Second law of thermodynamics yield best performance against the 45.14 percent and the rate of entropy production in this case equal to 0.099 kW/K respectively.
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