Market demands with their multitude of stimuli and information can be particularly overwhelming for children, whose cognitive abilities and skills are not yet fully developed and who lack market experience and knowledge (Mau et al., 2014). To better understand children’s purchase decisions, associated behaviors, and deficits, Mau et al. (2016) analyzed children’s behaviors in a simulated supermarket environment. They showed that children often behave differently at the point of sale than they intended and expected to when making their purchase decision. Slightly more than half of the children indicated that they would primarily look for low prices when shopping. Although the children in the subsequent observation of their shopping behavior had a limited budget and were tasked with buying the cheapest products, it was found that they clearly tended to select products more based on package design or brand. These findings indicate that children have difficulty implementing a basic requirement of goal-oriented consumer behavior, namely, taking the right actions to achieve a set goal (Bagozzi & Dholakia, 1999).

Regarding the question of how actions in purchasing processes could be implemented in a goal-oriented manner, we draw on basic theoretical frameworks of action regulation that include feedback loops, such as the cybernetic TOTE model (Powers, 1973). Carver and Scheier (1981) assume that the successful realization of a goal state (e.g., fulfillment of the shopping list) occurs by passing through loops in which the existing and target states (e.g., contents of the shopping cart vs. the shopping list) are repeatedly compared with each other and a deviation is successively reduced by operations until the loop is exited. Consequently, the execution of action is expressed as a sequence of corresponding operations and is always in the interplay between the goals of the agent and the situational requirements. According to Gillebaart (2018), setting standards or goals as well as monitoring deviations are aspects of self-regulation, while successful self-control comes into play within the feedback loop in the ‘operate’ phase. Self-control has been described by Baumeister et al. (2007) as the mental processes that enable people to control their thoughts, emotions, and behaviors to achieve higher-level goals. While operating, various aspects of self-control can be observed, such as suppressing the impulse to be tempted by alluring stimuli that are not in line with our long-term goals (e.g., completing the shopping list), avoiding situations that might lead one into temptation (e.g., forgo the candy shelf), or even delaying gratification with an immediate, smaller reward in order to obtain a larger, delayed reward. According to Inzlicht et al. (2014), as a result of repeated self-control efforts, there may be a change in the degree of self-control displayed. This is attributed to a change in task priorities, a shift in motivation away from so-called "have-to" to "want-to" goals that provide more pleasure and satisfaction. Therefore, the process of action regulation is always under the influence of changing motivations and the attendant changes in emotions and attention. Although self-control has been highlighted in its importance for the successful implementation of consumer goals (e.g., by avoiding impulsive purchases; Baumeister, 2002), there is still no study that specifically captures children's operations in the purchasing process and relates the extent of self-controlled behavior to the successful implementation of a purchase intention.

To address this gap, we used a computer-based supermarket simulation to study children's shopping behavior at the point of sale. In this task, children were asked to complete a shopping task based on a shopping list in the supermarket simulation. The supermarket simulation is designed so that, at the behavioral level, children's attentional behavior can be inferred from the log data of the computer-based task (Silberer, 2009). Attentional behavior includes observable attention to objects in the store environment, i.e., how often or how long children look at individual products. The supermarket simulation was intentionally designed to include elements that are not required for the performance task. The extent to which children engage with these irrelevant elements can be gauged from their attentional behavior and, at the behavioral level, enables differentiation between actions that are more conducive to have-to goals (as defined by the task) or want-to goals as defined by Inzlicht et al. (2014). The data analysis focused on whether the covariance among behavioral indicators hypothesized to capture self-control (e.g., the extent of engagement with task-irrelevant products) could be explained by a single common factor and how that factor was related to task success, monitoring of task performance, and spending. A sample of 136 elementary school children was given a shopping list and a limited budget. To extract behavioral indicators from the log data, we used the finite-state machine approach (Kroehne & Goldhammer, 2018).

A one-dimensional confirmatory factor analysis (CFA) with all assumed indicators was conducted. The model for self-control included four variables: The temporal extent to which children paid attention to irrelevant shelves (S1) or products (S2), the frequency with which they purchased irrelevant products that were not on the shopping list (S3), or visited irrelevant shelves (S4). The model showed a largely good fit (χ2(1) = 2.276, p = .131, RMSEA = 0.105, 90% RMSEA CI [.000, .294], CFI = 0.993, TLI = 0.956, SRMR = .04). Only the RMSEA exceeded the cut-off criterion. Task success was estimated using the partial credit model. The significant correlation between task success (WLE) and the factor for self-control (r(113)=.44, p<.001) indicates that self-control plays an important role in the purchase process. Our results also show that children who monitored their spending (imprecision of estimates, r(108)= -.35, p<.001) and task success (r(111)=.40, p<.001) more carefully tended to show greater self-control in task performance. Our study illustrates how theory-based factors can be extracted from log data of computerized tasks and demonstrates their diagnostic potential, which can be used to improve the quality and richness of psychological and educational assessments.

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