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Empirically derived recommendations for personalised text-based technical support

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dc.contributor.author Gizaw,Tulu Solomon
dc.contributor.author Buckley, Jim
dc.contributor.author Beecham, Sarah
dc.date.accessioned 2017-02-06T16:40:13Z
dc.date.available 2017-02-06T16:40:13Z
dc.date.issued 2016
dc.identifier.uri http://hdl.handle.net/10344/5502
dc.description peer-reviewed en_US
dc.description.abstract Technical Support (TS) is a post sales service provided to users of Information Technology (IT) products. Effective customer support can increase an IT company's revenue, improve the quality of their software, build customer loyalty, and enhance their reputation. However, not all companies realise these benefits as many customers and users are choosing alternative forms of support such as open source non-proprietary support forums.This paper posits that this movement to forums is because of a perceived improvement in service levels and thus presents a study of empirically-derived practices for Technical Support (TS) from these forums. In this analysis we identified types of users (personas) and grouped them according to levels of expertise and what they value. Additionally we identified characteristics of the communication handling process that influence desirable and undesirable outcomes. Focussing solely on text based support, we present ways that TS advisors can identify user types and, having identified the user type, how to tailor their response accordingly. Finally, we also indicate how ignoring user-types or through inappropriate handling of a question, the TS advisor/user interaction can fail. en_US
dc.language.iso eng en_US
dc.publisher Springer en_US
dc.relation.ispartof Empirically Derived Recommendations for Personalised Text-Based Technical Support en
dc.relation.ispartofseries 16th International Conference, SPICE 2016; Communications in Computer and Information Science;609, pp. 313-333
dc.relation.uri http://dx.doi.org/10.1007/978-3-319-38980-6_23
dc.rights The original publication is available at www.springerlink.com en_US
dc.subject information technology en_US
dc.subject technical support en_US
dc.subject user characteristics en_US
dc.subject online technical support forums en_US
dc.subject individuaisation en_US
dc.subject human factors en_US
dc.title Empirically derived recommendations for personalised text-based technical support en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.date.updated 2017-02-06T16:22:21Z
dc.description.version ACCEPTED
dc.identifier.doi 10.1007/978-3-319-38980-6_23
dc.contributor.sponsor SFI en_US
dc.relation.projectid 10/CE/I1855 en_US
dc.relation.projectid 07/CE/I1142 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.rssid 2643351
dc.internal.copyrightchecked Yes
dc.description.status peer-reviewed


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