About time. A motivation-based complementary framework for temporal dynamics in Web personalization
| Date | 13 May 2019 |
| DOI | https://doi.org/10.1108/JSIT-06-2017-0042 |
| Pages | 236-254 |
| Published date | 13 May 2019 |
| Author | Ville Salonen,Heikki Karjaluoto |
| Subject Matter | Information & knowledge management |
About time
A motivation-based complementary framework
for temporal dynamics in Web personalization
Ville Salonen
Department of School of Business and Economics, University of Jyväskylä,
Jyväskylä, Finland, and
Heikki Karjaluoto
Department of Marketing, University of Jyväskylä, Jyväskylä, Finland
Abstract
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
highlightthe benefits of considering user motivationwhen addressing issues in temporal dynamics.
Design/methodology/approach –Through theory, a complementary framework and propositions for
motivation-based temporaldynamics 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 suggestedframework distinguishes two ways(identifying/learning andshifting) 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
predominantlysupport both the frameworkand the tested propositions.The theoretical basis forthe approach
pavesa path towards refined psychologicaluser models; however,currently on a complementarylevel.
Research limitations/implications –While the frameworkis validated throughfeeding back findings,
and someof the propositions are validatedthrough basic experimentation,further empiricaltesting 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 usermotivation.
Keywords Timing, Temporal dynamics, Fundamental motives framework, Preference matching,
Web personalization
Paper type Conceptual paper
Introduction
Web personalisation requires the matching of user preferences by delivering the right
option at the right time (Tam and Ho, 2005). However, when is the time right? Despite
its centrality to the practice of web personalisation (Koren, 2010), timing –or temporal
dynamics –has received insufficient attention in the literature (Ho et al., 2011;Huang
© Ville Salonen and Heikki Karjaluoto. Published by Emerald Publishing Limited. This article is
published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce,
distribute, translate and create derivative works of this article (for both commercial and non-
commercial purposes), subject to full attribution to the original publication and authors. The full
terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Funding from the Finnish Funding Agency for Technology and Innovation TEKES is greatly
appreciated.
JSIT
21,2
236
Received6 June 2017
Revised28 November 2018
9 February2019
25March 2019
Accepted6 May 2019
Journalof Systems and
InformationTechnology
Vol.21 No. 2, 2019
pp. 236-254
EmeraldPublishing Limited
1328-7265
DOI 10.1108/JSIT-06-2017-0042
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1328-7265.htm
and Zhou, 2018;Salonen and Karjaluoto, 2016).Fewattemptshavebeenmadetoeither
effectively produce a real-time model that considers the effects of changing intentions
(Ding et al., 2015) and cognitive styles (Hauser et al., 2014) or to develop methods for
adapting to these. We wish to continue this development by expanding on the
psychology of shifting preferences.
Temporal dynamics in web personalisation refers to user preferences changing with
time. Here, time is primarily a context for interaction(Ho et al.,2011), which could be termed
either situational or contextualtime. The element of timing presents many problems for web
personalisation practices. For example, because preferences are in flux (Simonson, 2005),
timing requires an understanding of the user’s immediate context, which is often different
from that of the long-term user profile (Jannach et al.,2015). In addition, understanding,
predicting and activating such contextual effects require refined psychological models
(Salonen and Karjaluoto, 2016). Matchingpreferences can also become increasingly difficult
when no prior user profile exists. In such cases, recommendations are based on guesses at
best (Johar et al.,2014). Finally, it is difficult to grasp rapid changes using currently
available approaches(Ding et al., 2015).
Previous studies that have investigated timing effects in web personalisation and web
adaptation have been fruitful (Bodoff and Ho, 2014;Bogina et al.,2016;Ding et al., 2015;
Hauser et al.,2009,2014;Ho et al.,2011;Hong et al.,2012;Jannach et al., 2015,2017;Koren,
2010;Lambrecht and Tucker, 2013;Li et al., 2014;Pereira et al., 2018;Urban et al.,2013).
However, these studiespredominantly focussed on long-term changes rather than on having
more immediate effects (Hong et al., 2012) built upon a rational view of user behaviour (Ho
et al.,2011)or neglected contextual factors (Li et al., 2014). Therefore, a framework that also
captures more immediatecontextual effects is needed.
Although recent advances have been made towards effective real-time modelling
(Ding et al., 2015;Hauser et al., 2014;Jannach et al., 2015,2017;Pereira et al., 2018), these
models have mostly been built via simple psychological modelling. For instance, Ding
et al. (2015) found encouraging results for their real-time intent-based model, which was
based on the stimulus-organism-response (SOR) framework. However, the SOR
framework does not provide specific answers regarding when, why and how a certain
stimulus is likely to affect a user’s choices. Similarly, Hauser et al. (2014) based on their
real-time approach on cognitive styles, which could possibly benefit from considering
the interplay between motivation and preferences. Hence, we wish to provide the first
steps towards more refined psychological models to enable an enhanced psychological
fit in web personalisation.
Although preferences are state dependent (Zhang, 2013) and motivation is driven
(Griskeviciusand Kenrick, 2013), motivation-based approacheshave been lacking in the web
personalisation literature (Salonen and Karjaluoto, 2016). While Pappas et al. (2017) and
Huang and Zhou (2018) have recently found encouraging results based on both complexity
theory and uses and gratification theory, we envision a more effective approach by using a
motivationalframework that:
fully acknowledges chronic (long-term) and situational (short-term) effects; and
provides a detailed list of expected behavioural tendencies.
Therefore, we suggest a motivation-basedapproach that relies on the fundamental motives
framework (FMF) (Griskevicius and Kenrick, 2013;Kenrick et al., 2010a,2010b). In this
article, we suggest that applying the FMF to web personalisationenables both explanatory
advances and practicalinferences as follows:
Temporal
dynamics in
Web
personalization
237
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