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The purpose of this study is to empirically examine the utility of information systems (IS) success models in mandatory e-government services, as opposed to the volitional…
The purpose of this study is to empirically examine the utility of information systems (IS) success models in mandatory e-government services, as opposed to the volitional ones that have been the focus of previous studies. The models include the technology acceptance model (TAM) (1989) and Seddon’s model (1997), which involve three (ease of use, usefulness and citizens satisfaction) and four variables (system quality, information quality, usefulness and citizen satisfaction).
The models were compared based on a survey conducted on 780 foundation year students of government universities in Saudi Arabia. The Saudi Government has launched a mandatory e-government service geared to assist high school graduates in the university academic admission process. The goodness-of-fit and parsimony of fit indices and the explanatory power were used to compare the two models.
The structural equation modeling techniques revealed that overall, the two models both exhibited reasonable fit with the collected data, whereas TAM showed the best fit to the sample data and yielded superior goodness-of-fit indices over Seddon’s model. In terms of explanatory power, Seddon’s model predicted 28% (R2 = 0.28) of the variance explained for citizen satisfaction, whereas TAM predicted 21% (R2 = 0.21). All the parsimony of fit indices favored TAM over Seddon’s model.
This study examined the validity of TAM and Seddon’s model, using citizen satisfaction as the dependent variable to compare them. TAM and Seddon’s model were modified to better fit the current research context of mandatory e-government services; thus, the findings may not hold for their original or other voluntary settings. In addition, the focus on a single survey for a certain time in a certain territory of mandatory e-government service may have limited the generalizability of the results to other mandatory contexts. Future research should make use of large, cross-sectional samples in different mandatory contexts to enhance result generalization.
This study’s findings can provide e-government practitioners with deeper perceptions of how to address citizen satisfaction with mandatory e-government services. The results exposed usefulness as the common and major construct, having the strongest influence on citizen satisfaction in both TAM and Seddon’s model; thus, maximizing the benefits of e-government services for citizens is crucial to their success. The causal relationship between information quality and citizen satisfaction was not supported. This supports the perspective that e-government services are currently evolving quickly, becoming more integrated and easier-to-use, generally requiring only a few clicks and less information.
This study has extended the assessment of the validity of IS success models to a mandatory IS usage setting. The comparison study of different IS success models is crucial as it acts as a guide for researchers to determine the trade-off between the models used to conduct research on a particular context. The study concludes that TAM is the most parsimonious and universal model for the study of user satisfaction in mandatory contexts. The findings will provide e-government practitioners with insights into IS success measures suited to enhance the effectiveness of newly and future mandated e-government services.
Recent studies indicated that the level of adoption of health data standards in healthcare organisations remains frustratingly low worldwide although health data standards…
Recent studies indicated that the level of adoption of health data standards in healthcare organisations remains frustratingly low worldwide although health data standards have been perceived to be an essential tool for interoperability barriers within health information systems. The relevant literature still lacks significant studies concerning the issues of the adoption process of health data standards in healthcare organisations, and in particular those in developing nation. In addressing this gap in knowledge, the purpose of this paper is to investigate the adoption decision of health data standards in tertiary healthcare organisations in Saudi Arabia, and to develop a technology-organisation-environment list that contains the critical factors influencing their adoption.
A multiple-case study methodology was conducted in Saudi Arabia and different data collection methods were used included semi-structured interviews with different decision makers at various levels and departments of the subject organisations, and documents analysis to identify critical factors to the adoption decision of health data standards.
The findings demonstrated a list of key factors from different aspects impacting the adoption decision of health data standards in the subject organisations. The technological factors are complexity and compatibility of health data standards, IT infrastructure, switching costs, market uncertainties, systems integration and enhancing the use of advanced systems. The main organisational factors are the lack of adequate policies and procedures and information management plan, resistance to change, data analysis and accreditation. The core environmental factors are the lack of national regulator and data exchange plan, national healthcare system and the shortage of professionals.
The results from the qualitative data were difficult to generalise to other populations. For example, the structure of the health sector varies from country to country as each health sector has its own characteristics that affect and are affected by national circumstances. In order to provide a more grounded theory resulting from a qualitative study, further examination by conducting quantitative studies is required. In addition, the TOE approach does not take into account the sociotechnical issues and further research is required in this area.
The investigation into the adoption decision of health data standards in tertiary healthcare organisations in Saudi Arabia has led to the development of a technology-organisation-environment list that contains the critical factors influencing their adoption. The research outcome has addressed the gap in knowledge of the adoption of health data standards in healthcare organisations. It also provides the decision maker, and in particular those in developing nations, with better understanding of the adoption process of those standards to better judge and to develop suitable strategy of adoption interventions.
Although recent studies indicated that the level of adoption of health data standards in healthcare organisations remains frustratingly low, the prior studies related to health data standards missed out on the exploration of the adoption decision of different types of health data standards in healthcare organisations and the critical factors influencing their adoption. Research on health data standards adoption based out of a developing country such as Saudi Arabia can also potentially provide several new insights on standards practices.