Who reads customer reviews after product choice? Maximizing, satisficing, and postchoice information search

Kim, Ka-Eun

doi:10.1016/j.paid.2021.111192

Cited by 10 publications

(5 citation statements)

References 61 publications

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“…From a theoretical perspective, we extend the emerging, but still limited, literature on the link between a maximizing decision‐making style and consumer well‐being. In particular, a plethora of prior studies have focused on the impact of maximizing on individuals' prepurchase, in‐purchase, and postpurchase consumption behavior (Besharat et al, 2014; Carrillat et al, 2011; Kim, 2022; Polman & Maglio, 2022). While consumers have to balance consumption behavior with savings behavior to maximize utility during their life cycle (Browning & Crossley, 2001), insights are still lacking on how maximizing affects individuals' financial well‐being .…”

Section: Discussionmentioning

confidence: 99%

When “good enough” is not good enough: How maximizing benefits financial well‐being

Silber,

Hoffmann,

Belli

2023

Psychology and Marketing

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A maximizing decision‐making style is generally associated with lower individual well‐being. That is, even though maximizers invest more time and resources in finding the best option and achieve better outcomes than satisficers, they are still more dissatisfied with those outcomes. Contrary to this general consensus that maximizing is negatively associated with overall well‐being, across two studies we show that this decision‐making style is actually positively associated with individuals' financial well‐being. We find that measured dispositional maximizing is positively associated with financial well‐being, regardless of whether maximizing is operationalized as having high standards or the tendency to engage in alternative search (Study 1) and replicate this relationship with experimentally induced situational maximizing (Study 2). We identify financial self‐control (both measured as a trait and as the behavioral outcome of an experimental choice task) as a mediator of the aforementioned relationship. Our findings offer guidance to financial service providers and policymakers on how to improve consumers' financial well‐being, such as encouraging consumers to engage in a more meticulous search while evaluating financial products and services (e.g., home loans, retirement plans, investments) to identify the best possible option.

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Section: Discussionmentioning

confidence: 99%

When “good enough” is not good enough: How maximizing benefits financial well‐being

Silber,

Hoffmann,

Belli

2023

Psychology and Marketing

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“…Second, maximizing comprises two facets: the pursuit of the best possible choice (goal) and an extensive search for alternatives (search) [34]. Depending on which of the two factors dominates, maximizing individuals could experience positive or negative affective states [35][36][37][38]. For example, Kim [38] found that the search aspect of maximizing is related to seeking both negative and positive customer reviews after product choice, which decreases the level of satisfaction.…”

Section: Limitations and Future Research Directionsmentioning

confidence: 99%

“…Depending on which of the two factors dominates, maximizing individuals could experience positive or negative affective states [35][36][37][38]. For example, Kim [38] found that the search aspect of maximizing is related to seeking both negative and positive customer reviews after product choice, which decreases the level of satisfaction. However, the goal aspect of maximizing is related to seeking positive customer reviews after product choice, and this does not decrease consumers' satisfaction.…”

Section: Limitations and Future Research Directionsmentioning

confidence: 99%

Maximizers’ Reactance to Algorithm-Recommended Options: The Moderating Role of Autotelic vs. Instrumental Choices

Kim

2023

Behavioral Sciences

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The previous literature has provided mixed findings regarding whether consumers appreciate or are opposed to algorithms. The primary goal of this paper is to address these inconsistencies by identifying the maximizing tendency as a critical moderating variable. In Study 1, it was found that maximizers, individuals who strive for the best possible outcomes, exhibit greater reactance toward algorithm-recommended choices than satisficers, those who are satisfied with a good-enough option. This increased reactance also resulted in decreased algorithm adoption intention. Study 2 replicated and extended the findings from Study 1 by identifying the moderating role of choice goals. Maximizers are more likely to experience reactance to algorithm-recommended options when the act of choosing itself is intrinsically motivating and meaningful (i.e., autotelic choices) compared to when the decision is merely a means to an end (i.e., instrumental choices). The results of this research contribute to a nuanced understanding of how consumers with different decision-making styles navigate the landscape of choice in the digital age. Furthermore, it offers practical insights for firms that utilize algorithmic recommendations in their businesses.

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“…Although various theoretical and methodological approaches to maximization have been suggested (see Cheek & Schwartz, 2016), in the last two decades numerous studies have evidenced its impact on decision-making. Maximization has been associated with higher reliance on normative principles than on intuition (Misuraca et al, 2021), rumination on the choice after it has been made (Kim, 2022), and procrastination .…”

Section: Maximization In Decision-makingmentioning

confidence: 99%

‘Let’s be Careful out There’: Maximization and Core Values Predict Action Time in Police Decision Making

Tejeiro

Alison

González

et al. 2023

Preprint

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Who reads customer reviews after product choice? Maximizing, satisficing, and postchoice information search

Cited by 10 publications

References 61 publications

When “good enough” is not good enough: How maximizing benefits financial well‐being

When “good enough” is not good enough: How maximizing benefits financial well‐being

Maximizers’ Reactance to Algorithm-Recommended Options: The Moderating Role of Autotelic vs. Instrumental Choices

‘Let’s be Careful out There’: Maximization and Core Values Predict Action Time in Police Decision Making

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