A hybrid approach to develop an analytical model for enhancing the service quality of e-learning

2012 ◽  
Vol 58 (4) ◽  
pp. 1318-1338 ◽  
Author(s):  
Hung-Yi Wu ◽  
Hsin-Yu Lin
Author(s):  
Mohamad Haidar

The purpose of this chapter is to discuss the public perception of the quality of service in the public transit system in Montreal using a combination of analyses and surveys. The results are used to make recommendations to improve the STM and its perception. General guidelines of SERVQUAL with some additional questions that are more specific to the current social environment of the city are presented. A survey was conducted by asking 250 international graduate Concordia students to rate a series of statements based on the importance of the issue and how much they agreed with the statement, the results were analyzed using three methods: SERVQUAL, SERVPERF, and IPA. The improvement of timetable synchronization between different metro lines and buses is crucial, as well as the education of STM employees in terms of dealing with different ethnicities, languages, and backgrounds are found. The chapter is a rare outside look at the STM and how users perceive the quality of the service, as opposed to the usual internal studies done by the organization itself.


2020 ◽  
Vol 4 (2) ◽  
pp. 141
Author(s):  
Elsi Puspita Sari ◽  
Sukardi Sukardi

The University of Padang (UNP) is one of the educational institutions in implementing e-learning. This research used quantitative method. The researcher evaluated e-learning by using the information success system DeLone & McClean model. This research was expected to be able to find out the overview of UNP e-learning. Based on data analysis, it showed that respondents’ level of achievement (TCR) reached 88.07% was categorized into good. The quality of information showed that the TCR reached 87.36% was categorized into good. Service quality of TCR reached 87.76% was categorized into good. The use that TCR reached 88.24% was categorized into good. Respondents’ satisfaction showed that TCR reached 88.73% was categorized into good. The benefit of TCR reached 84.10% was categorized into good. So, e-learning of Padang University had "Good" measurement on all variables, of course it would affect the use of e-learning itself, especially managed by educators and students' use.


2021 ◽  
Vol 10 (1) ◽  
pp. 134-140
Author(s):  
Kristophorus Hadiono ◽  
Novita Mariana ◽  
Rina Candra Noor Santi

The Covid-19 pandemic that has occurred to date has made learning activities that are usually carried out face-to-face, switch to networks by utilizing e-learning media. The transfer of learning activities to e-learning media has advantages and disadvantages so that it needs to be evaluated. This evaluation is carried out to see to what extent the service quality of e-learning media is used in learning activities. One way to assess service quality is using the e-service quality method. The purpose of this study was to determine the quality of e-learning services. The service quality assessment factors used in this study are tangibility, reliability, responsiveness, assurance, and empathy. The research method used in this research is quantitative method and the data collection period starts from August 2020 to February 2021. 174 students was participated in this study, with the largest proportion being semester 7 students. The instrument used has good validity with a KMO value of more than 0, 5 and is reliable with a Cronbach's alpha value of more than 0.6. The final results of the study can be concluded that five factors measuring the quality of electronic services can be used to measure the quality of electronic learning services and the most influential factor is the assurance factor.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ajith Tom James

PurposeThe purpose of this paper is to develop a framework for benchmarking the service quality of amusement parks.Design/methodology/approachA hybrid approach, which is a combination of AHP (analytic hierarchy process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), is applied for service quality benchmarking.FindingsAmusement parks are centers of attraction at various tourist destinations across the world. Their service quality is constituted by the attainment of certain quality attributes that varies with different parks. For sustaining in the industry, the managers of the parks need to have a good overview of the practices followed by them and their competitors that necessitate benchmarking of the service quality.Practical implicationsThe developed framework using the hybrid methodology of AHP and TOPSIS can be applied for comparing different amusement parks based on quality attributes, which will help the organizers in improving their service quality.Originality/valueThe paper identifies various service quality attributes of amusement parks and an evaluation scheme for those attributes had been developed. Based on these, a framework had been developed for benchmarking of service quality of different amusement parks.


Author(s):  
Long Pham ◽  
Stan Williamson ◽  
Ronald Berry

With the growing ubiquity of the Internet and the continued evolution of the Internet of Things, universities are focusing more on web-based strategies to deliver higher education (i.e., e-learning). In spite of this, few studies on e-learning service quality have been conducted to examine the effectiveness of these efforts. This study seeks to identify primary e-learning service quality dimensions and to examine the relationships among e-learning service quality dimensions, overall e-learning service quality, e-learning satisfaction and e-learning loyalty as perceived by e-students in the college setting. Results identified five main factors that measure e-learning service quality: e-learning administrative and support service quality; e-learning instructor quality; e-learning accuracy; e-learning course materials quality; and e-learning security and privacy. The quality of e-learning administrative and support service, instructor performance, and course materials were positively related to overall e-learning service quality, with e-learning instructor quality the most influential. There was a positive association between overall e-learning service quality and e-learning loyalty, and between e-learning satisfaction and e-learning loyalty. Results are consistent with most studies of traditional and online services and other e-learning studies that customer loyalty is strongly influenced by customer satisfaction and quality of service and that customer satisfaction is strongly influenced by quality of service.


2019 ◽  
Vol 19 (2) ◽  
pp. 153-166
Author(s):  
Ferry Susanto

This study aims to identify factors - factors that affect the level of user acceptance of e-learning in STMIK Surya Intan Kotabumi by lecturers as users, teachers and content developers. This study uses a model approach Unified Theory of Acceptance and Use of Technology (UTAUT) and models - other models. Model UTAUT dimofikasi by adding some variables to refer to the study - previous research. Variables used include performance expectancy, social influence, facilitating conditions, self-efficacy, information quality, system quality, service quality, behavioral intention, actual use and moderator usia..Langkah-step analysis of factors - factors is making a questionnaire derived from the model UTAUT, alter the results of a questionnaire by the method of successive interval (MSI). Furthermore, analysis of data using Structural Equation Modeling with Partial Least Square (PLS-SEM). PLS The data were processed using the application smartPLS. The results showed that only four variables that affect directly the use of e-learning (actual use) by lecturers at STMIK Surya Intan Kotabumi. These variables include interest for the use of e-learning (behavioral intention),influence the ability of professors to the use of e-learning (self-efficacy), influence the quality of information provided e-learning (information quality), and quality of service (service quality).Keyword : E-Learning, UTAUT, MSI, PLS-SEM, SmartPLS


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