6533b86dfe1ef96bd12cab43
RESEARCH PRODUCT
About time
Karjaluoto HeikkiVille Salonensubject
motivaatioMatching (statistics)General Computer Sciencefundamental motives frameworkComputer sciencetemporal dynamicsmieltymyksetmedia_common.quotation_subjectajoitus (suunnittelu)käyttäjäpsykologiaData sciencePreferencePersonalizationEmpirical researchpreference matchingOriginalityDynamics (music)web personalizationräätälöintiPractical implicationsverkkopalvelutInformation Systemsmedia_commondescription
Purpose The purpose of this paper seeks to develop a motivation-based complementary framework for temporally dynamic user preferences to facilitate optimal timing in web personalisation. It also aims to highlight the benefits of considering user motivation when addressing issues in temporal dynamics. Design/methodology/approach Through theory, a complementary framework and propositions for motivation-based temporal dynamics for further testing are created. The framework is validated by feeding back findings, whereas some of the propositions are validated through an experiment. Findings The suggested framework distinguishes two ways (identifying/learning and shifting) of using a motive-based approach to temporal dynamics in web personalisation. The suggested outcomes include enhanced timing in matching current preferences and improved conversion. Validation measures predominantly support both the framework and the tested propositions. The theoretical basis for the approach paves a path towards refined psychological user models; however, currently on a complementary level. Research limitations/implications While the framework is validated through feeding back findings, and some of the propositions are validated through basic experimentation, further empirical testing is required. Practical implications A generalised approach for complementing personalisation procedures with motivation-based temporal dynamics is offered, with implications for both user modelling and preference matching. Originality/value This paper offers novel insights to web personalisation by considering the in-depth effects of user motivation.
year | journal | country | edition | language |
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2019-05-13 | Journal of Systems and Information Technology |