TY - JOUR
T1 - Nudging moods to induce unplanned purchases in imperfect mobile personalization contexts
AU - Ho, Shuk Ying
AU - Lim, Kai H.
N1 - Publisher Copyright:
© 2018 University of Minnesota. All rights reserved.
PY - 2018/9
Y1 - 2018/9
N2 - By tracking consumers' browsing and purchase history, web personalization generates taste-matched recommendations for each consumer to stimulate purchases. In addition to taste-matching, mobile personalization matches recommendations to a consumer's physiological need and current location. These two additional features, referred to as need-matching and location-matching, are believed to be enablers of unplanned purchases. However, mobile advertisers may not be able to generate recommendations that meet all personalization criteria. Hence, mobile recommendations may be imperfect. We examine two questions in relation to imperfect recommendations. First, how do we use a descriptor to promote such recommendations? Second, what personalization criterion should be downplayed to induce unplanned purchases? Drawing upon the theory of mood congruence, we theorize that the effect of imperfect recommendation on consumers' unplanned purchases depends on their mood. We conducted three field experiments to test our hypotheses. Our findings indicate that (1) consumers in positive moods are more likely to form an urge to buy than those in negative moods, and this difference is larger when the descriptor is partial than when it is complete (Experiment 1); (2) need-matching is more influential on urge to buy for consumers in negative moods than for those in positive moods (Experiment 2); and (3) for taste-and-need-matched recommendations, location-matching exerts a stronger effect on the urge to buy for consumers in negative moods than for those in positive moods (Experiment 3). We validated the relevance of our research findings to practice through interviews with senior executives in personalization solution providers. Pathways for enhancing practical impacts of this line of research are recommended.
AB - By tracking consumers' browsing and purchase history, web personalization generates taste-matched recommendations for each consumer to stimulate purchases. In addition to taste-matching, mobile personalization matches recommendations to a consumer's physiological need and current location. These two additional features, referred to as need-matching and location-matching, are believed to be enablers of unplanned purchases. However, mobile advertisers may not be able to generate recommendations that meet all personalization criteria. Hence, mobile recommendations may be imperfect. We examine two questions in relation to imperfect recommendations. First, how do we use a descriptor to promote such recommendations? Second, what personalization criterion should be downplayed to induce unplanned purchases? Drawing upon the theory of mood congruence, we theorize that the effect of imperfect recommendation on consumers' unplanned purchases depends on their mood. We conducted three field experiments to test our hypotheses. Our findings indicate that (1) consumers in positive moods are more likely to form an urge to buy than those in negative moods, and this difference is larger when the descriptor is partial than when it is complete (Experiment 1); (2) need-matching is more influential on urge to buy for consumers in negative moods than for those in positive moods (Experiment 2); and (3) for taste-and-need-matched recommendations, location-matching exerts a stronger effect on the urge to buy for consumers in negative moods than for those in positive moods (Experiment 3). We validated the relevance of our research findings to practice through interviews with senior executives in personalization solution providers. Pathways for enhancing practical impacts of this line of research are recommended.
KW - Imperfect recommendations
KW - Mobile personalization
KW - Mood
KW - Mood congruence
KW - Unplanned purchase
UR - http://www.scopus.com/inward/record.url?scp=85051711208&partnerID=8YFLogxK
U2 - 10.25300/MISQ/2018/14083
DO - 10.25300/MISQ/2018/14083
M3 - Article
SN - 0276-7783
VL - 42
SP - 757
EP - 778
JO - MIS Quarterly: Management Information Systems
JF - MIS Quarterly: Management Information Systems
IS - 3
ER -