Preference stability belief as a determinant of response to personalized recommendations

Abstract

Preference stability refers to the objectively measured choice consistency among options with different attribute values in the same product category. We suggest that a consumer's subjectively held belief of preference stability may be an important determinant of response to personalized recommendations. Experimental results confirm that preference stability belief moderates the effect of customization on the evaluation of recommendation accuracy and receptiveness to the learning relationship. Customization will produce stronger effects on accuracy evaluation and receptiveness for subjects with high preference stability belief than for subjects with low preference stability belief. Customers who believe their preferences are stable appreciate customized recommendations more, notice more acutely whether recommendations are customized or not, and are more receptive to the learning relationship when recommendations are customized than when not. Customers who believe their own preferences are less stable do not appreciate customized recommendations as much, are less sensitive to whether recommendations are customized or not, and are not more receptive to the learning relationship even when recommendations are customized. Theoretical and managerial implications of our findings are discussed.

Music discovery and revisiting behaviors of individuals with different preference characteristics: An experience sampling approach

“…Music involvement has its origin in the marketing literature (Zaichkowsky, , ), whereas diversity and openness were developed in our previous research on users' responses to personalized recommendations. Studies have shown that users' preference characteristics are crucial moderators between recommendation strategies and user satisfaction (Tang, Chang, & Lin 2018; Ferwerda, Graus, Vall, Tkalcic, & Schedl, ; Tang et al, ; Shen, ; Kwon, Cho, & Park, ; Simonson, ). Several notable observations emerged from the results of the logit and mixed regression models regarding differences between these music‐related psychological traits, modes of music access, and music enjoyment.…”

Message‐to‐person versus person‐to‐message: An alternative way to conceptualize personalized advertising

“…As seen in many prior studies, this two-phase approach of personalizing messages has been widely adopted in experimental settings (e.g., Beam, 2014;Kim & Sundar, 2012;Li, 2016;Maslowska et al, 2013;Shen & Ball, 2011;Wan, 2008). When a personalized message produced via such a two-phase process is compared to a generic message, it is generally more effective in attitudinal and behavioral outcomes (Kalyanaraman & Sundar, 2006).…”

“…Consistent with prior studies (e.g., Beam, 2014;Kim & Sundar, 2012;Li, 2016;Maslowska et al, 2013;Shen & Ball, 2011;Wan, 2008), a two-phase personalization process was adopted to create stimulus messages. Participants' preferences of different sports were measured and this information was used to construct both personalized and nonpersonalized ads.…”

“…Thus, the concept of personalization needs to be clearly defined before personalization process and personalization effects can be further discussed in this study. While personalized messages can be created based on various aspects of personal information such as names (Dijkstra, 2014), purchase needs (Aguirre, Mahr, Grewal, de Ruyter, & Wetzels, 2015), personality traits (Hirsh, Kang, & Bodenhausen, 2012), personalization is narrowly defined in this study as a communication process in which message senders design and deliver individualized messages to each message recipient based on his/her measured preferences (Beam, 2014;Kim & Sundar, 2012;Kramer, Spolter-Weisfeld, & Thakkar, 2007;Shen & Ball, 2011).…”

“…Message receivers may not always know their preferences and oftentimes they cannot articulate the preference information to message senders in a consistent way (Bettman, Luce, & Payne, 1998;Nisbett & Wilson, 1977;Simonson, 2005). It was shown in Shen and Ball (2011) that people were more receptive to personalized information only when they believed their preferences were stable. In a similar vein, Syam, Krishnamurthy, and Hess (2008) discussed people's "miswanting" behavior (people say they want something but later on find out that is not what they want).…”