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Although models exist that assess the QoE of Web Application, significant challenges remain in: (1) Defining QoE factors from a Web engineering perspective, (2) quantifying the relationship between so\u2010called \u201cobjective\u201d and \u201csubjective\u201d factors of relevance, and (3) dealing with limited data available in relation to subjective factors. In response, the work here presents a novel model (and associated software instantiation) that integrates factors through Key Performance Indicators and Key Quality Indicators. The mapping is incorporated into a correlation model that assesses the QoE of Web Applications, with a consideration of defining the factors in term of quality requirements derived from web architecture. The data resulting from the mapping is used as input of the proposed model to develop artefacts that quantify and predict QoE using Machine Learning. The development of proposed model is framed and guided by Design Science Research approach with the purpose of enabling providers to more informed decisions regarding QoE and\/or to optimise resources accordingly. Although the work is oriented at developing an artefact that has clear utility for practice, the nascent design theory underpinning the work is developed and discussed.<\/jats:p>","DOI":"10.1111\/isj.12192","type":"journal-article","created":{"date-parts":[[2018,3,6]],"date-time":"2018-03-06T03:26:37Z","timestamp":1520306797000},"page":"175-199","source":"Crossref","is-referenced-by-count":17,"title":["Developing a Quality of Experience (QoE) model for Web Applications"],"prefix":"10.1111","volume":"29","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-6290-8258","authenticated-orcid":false,"given":"Mark","family":"Lycett","sequence":"first","affiliation":[{"name":"School of Management, Royal Holloway University of London Egham Surrey TW20 0EX UK"}]},{"given":"Omar","family":"Radwan","sequence":"additional","affiliation":[{"name":"Department of Computer Science Brunel University London Uxbridge Middlesex UB8 3PH UK"}]}],"member":"311","published-online":{"date-parts":[[2018,3,5]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1057\/ejis.2008.43"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSEA.2010.62"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.5121\/ijdps.2013.4305"},{"key":"e_1_2_8_5_1","doi-asserted-by":"crossref","unstructured":"Aroussi S. &Mellouk A.(2014).Survey on machine learning\u2010based QoE\u2010QoS correlation models. 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