Understanding and predicting the quality determinants of e-government services

Abstract

Purpose – The purpose of this paper is to investigate the quality determinants influencing the adoption of e-government services in Oman and compare the performance of multiple regression and neural network models in identifying the significant factors influencing adoption in Oman. Design/methodology/approach – Primary data concerning service quality determinants and demographic variables were collected using a structured questionnaire survey. The variables selected in the design of the questionnaire were based on an extensive literature review. Factor analysis, multiple linear regression and neural network models were employed to analyze data. Findings – The study found that quality determinants: responsiveness, security, efficiency and reliability are statistically significant predictors of adoption. The neural network model performed better than the regression model in the prediction of e-government services’ adoption and was able to characterize the non-linear relationship of the aforementioned predictors with the adoption of e-government services. Further, the neural network model was able to identify demographic variables as significant predictors. Practical implications – This study highlights the importance of service quality in the adoption of e-government services and suggests that an enhanced focus and investment on improving quality of the design and delivery of e-government services can have a positive impact on the usage of the services, thereby enabling the Oman Government in achieving the governance objectives for which these technologies were employed. Originality/value – Studies in the area of e-government typically focus either on technology adoption problems or service quality problems. The role of service quality in adoption is rarely addressed. The research presented in this paper is of great value to the institutions that are involved in the development of technology-based e-government services in Oman.

The influence of transformed government on citizen trust: insights from Bahrain

“…Rodrigues, Sarabdeen, and Balasubramanian (2016) suggest that confidentiality, trust, and attitudes toward using technology are major factors for e-government adoption in the UAE. In Saudi Arabia, confidentiality, privacy, and security were identified as important factors for the successful implementation of e-government services (Yamin & Mattar, 2016); in addition to these factors, responsiveness, efficiency, and reliability were determined to be major factors in determining the quality of e-government (Sharma, Govindaluri, & Gattoufi, 2015). However, no study in the GCC has used trust as a dependent factor or assessed the impact of government transformation on citizen trust and confidence.…”

Applications of artificial neural networks in health care organizational decision-making: A scoping review

“…Neural networks have been used effectively as a tool in complex decision-making in strategic management, specifically in strategic planning and performance, assessing decision-making [96]. In health care, neural network models have been successfully used to predict quality determinants (responsiveness, security, efficiency) influencing adoption of e-government services [97]. With its ability to discover hidden knowledge and values, scholars have suggested using ANN to improve care performance and facilitate the adoption of ‘Lean thinking’ or value-based decision making in health care [87].…”

Evaluation of Government service quality from perspective of reliability

“…In this case, e-government service quality has been studied, such as the study of [36] proposed a model consisting of eight main dimensions "system quality, information quality, service quality, dispositional trust, institutional trust, interpersonal trust, continues intention, and EWOM intention". Study of [16] proposed e-government service quality model constructed of four main dimensions "responsiveness, security, efficiency, and reliability".…”