Citizens as consumers: Profiling e-government services' users in Egypt via data mining techniques
dc.contributor.author | Mostafa, MM | en |
dc.contributor.author | El-Masry, AA | en |
dc.date.accessioned | 2017-02-06T19:57:31Z | |
dc.date.available | 2017-02-06T19:57:31Z | |
dc.date.issued | 2013-01-01 | en |
dc.identifier.issn | 0268-4012 | en |
dc.identifier.uri | http://hdl.handle.net/10026.1/8363 | |
dc.description.abstract |
This study uses data mining techniques to examine the effect of various demographic, cognitive and psychographic factors on Egyptian citizens' use of e-government services. Data mining uses a broad family of computationally intensive methods that include decision trees, neural networks, rule induction, machine learning and graphic visualization. Three artificial neural network models (multi-layer perceptron neural network [MLP], probabilistic neural network [PNN] and self-organizing maps neural network [SOM]) and three machine learning techniques (classification and regression trees [CART], multivariate adaptive regression splines [MARS], and support vector machines [SVM]) are compared to a standard statistical method (linear discriminant analysis [LDA]). The variable sets considered are sex, age, educational level, e-government services perceived usefulness, ease of use, compatibility, subjective norms, trust, civic mindedness, and attitudes. The study shows how it is possible to identify various dimensions of e-government services usage behavior by uncovering complex patterns in the dataset, and also shows the classification abilities of data mining techniques. © 2013 Elsevier B.V. | en |
dc.format.extent | 627 - 641 | en |
dc.language.iso | en | en |
dc.title | Citizens as consumers: Profiling e-government services' users in Egypt via data mining techniques | en |
dc.type | Journal Article | |
plymouth.issue | 4 | en |
plymouth.volume | 33 | en |
plymouth.publication-status | Published | en |
plymouth.journal | International Journal of Information Management | en |
dc.identifier.doi | 10.1016/j.ijinfomgt.2013.03.007 | en |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA17 Business and Management Studies | |
dc.rights.embargoperiod | Not known | en |
rioxxterms.versionofrecord | 10.1016/j.ijinfomgt.2013.03.007 | en |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | en |
rioxxterms.type | Journal Article/Review | en |