This study aims to explore the influence of fuel price, electricity price, fuel consumption (FC) on operating cost, generation and operating income (OI), and how to get the…
Abstract
Purpose
This study aims to explore the influence of fuel price, electricity price, fuel consumption (FC) on operating cost, generation and operating income (OI), and how to get the optimized electricity generation (EG) through the operation plants mix economically.
Design/methodology/approach
This study is the kind of explanatory research that describes the influence of dependent variable on the independent variable through hypothesis testing. The unit of analysis in this study is PT PLN (Persero) data, and the data is represented by the company’s statistical data from 2004 to 2019. The inferential statistical method is used to analyse the variance in this study-based or component-based with partial least square using the software of SmartPLS 3.2.9.
Findings
The fuel price of generation has a positive significant effect on the average electricity price in both models, a negative significant effect on the FC in model A and a positive significant effect in model B, a positive significant effect on the EG in the model A and negative significant effect in the model B, a positive significant effect on the operating cost of generation in both models, and a positive significant effect on OI in both models also.
Originality/value
To the best of the author’s knowledge, this paper is the first to study the influence of generation fuel price, electricity price, FC on operating cost, EG and OI of the power company and using a complex research design with partial least square.
Details
Keywords
Wahyu Rafdinal, Nono Wibisono and Lina Setiawati
The massive adoption of virtual reality (VR) applications has started since the COVID-19 pandemic, and until now, VR applications are still being used. However, there is limited…
Abstract
Purpose
The massive adoption of virtual reality (VR) applications has started since the COVID-19 pandemic, and until now, VR applications are still being used. However, there is limited research that analyses the consumer's perspective on the adoption of VR applications. Thus, this study discovers the adoption of VR applications in the hospitality sector by integrating the value-based adoption model (VAM) and VR quality.
Design/methodology/approach
The data were gathered through a survey of 500 respondents and evaluated through the structural equation model-partial least squares (SEM-PLS).
Findings
Employing SEM-PLS and importance-performance map analysis (IPMA), the findings revealed that VR quality and perceived value are essential determinants in the adoption of VR applications in the hospitality industry.
Practical implications
Practically, this study encourages the hospitality industry to create and develop high-quality VR application technology to benefit visitors. Through this study, hospitality marketing managers, governments and others concerned with the hospitality industry’s future development can create effective ways to increase the adoption of VR applications in this industry.
Originality/value
This study offers novel perspectives into the theory and application of VR quality and VAM in the adoption of VR applications in the hospitality industry.