Junhui Li^1,*, Jinxin Zhong¹, Kailiang Wang¹, Yu Luo¹, Qian Han², Jieren Tan²

Energy Engineering, Vol.120, No.4, pp. 869-884, 2023, DOI:10.32604/ee.2023.021320 - 13 February 2023

Abstract In the process of wind power, coal power, and energy storage equipment participating in the operation of industrial microgrids, the stable operation of wind-storage industrial microgrids is guaranteed by considering demand response technology and user satisfaction. This paper firstly sorts out the status quo of microgrid operation optimization, and determines the main requirements for user satisfaction considering three types of load characteristics, demand response technology, power consumption benefit loss, user balance power purchase price and wind power consumption evaluation indicators in the system. Secondly, the operation architecture of the windstorage industrial microgrid is designed, and… More >

Jang Hyun Kim^1,2,3, Jisung Jang^1,3, Yonghwan Kim⁴, Dongyan Nan^1,2,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3815-3826, 2022, DOI:10.32604/cmc.2022.029507 - 16 June 2022

Abstract This study explored user satisfaction with mobile payments by applying a novel structural topic model. Specifically, we collected 17,927 online reviews of a specific mobile payment (i.e., PayPal). Then, we employed a structural topic model to investigate the relationship between the attributes extracted from online reviews and user satisfaction with mobile payment. Consequently, we discovered that “lack of reliability” and “poor customer service” tend to appear in negative reviews. Whereas, the terms “convenience,” “user-friendly interface,” “simple process,” and “secure system” tend to appear in positive reviews. On the basis of information system success theory, we… More >

Seon Hong Lee¹, Haein Lee¹, Jang Hyun Kim^2,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4983-4997, 2022, DOI:10.32604/cmc.2022.027943 - 21 April 2022

Abstract Metaverse is one of the main technologies in the daily lives of several people, such as education, tour systems, and mobile application services. Particularly, the number of users of mobile metaverse applications is increasing owing to the merit of accessibility everywhere. To provide an improved service, it is important to analyze online reviews that contain user satisfaction. Several previous studies have utilized traditional methods, such as the structural equation model (SEM) and technology acceptance method (TAM) for exploring user satisfaction, using limited survey data. These methods may not be appropriate for analyzing the users of… More >

Mohammed Hadwan^1,2,3,*, Mohammed A. Al-Hagery⁴, Mohammed Al-Sarem⁵, Faisal Saeed^5,6

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4675-4689, 2022, DOI:10.32604/cmc.2022.027311 - 21 April 2022

Abstract Different types of pandemics that have appeared from time to time have changed many aspects of daily life. Some governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during lockdown. The Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store. A huge number of reviews are written daily by users to express their opinions, which include significant information to improve these applications. The manual processing and extracting of information… More >

Jang Hyun Kim^1,2, Dongyan Nan^1,*, Yerin Kim², Min Hyung Park²

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2819-2829, 2021, DOI:10.32604/cmc.2021.014922 - 01 March 2021

Abstract As of 2020, the issue of user satisfaction has generated a significant amount of interest. Therefore, we employ a big data approach for exploring user satisfaction among Uber users. We develop a research model of user satisfaction by expanding the list of user experience (UX) elements (i.e., pragmatic, expectation confirmation, hedonic, and burden) by including more elements, namely: risk, cost, promotion, anxiety, sadness, and anger. Subsequently, we collect 125,768 comments from online reviews of Uber services and perform a sentiment analysis to extract the UX elements. The results of a regression analysis reveal the following:… More >