## 6 Discussion  
Our results revealed that a transparent RA together with low cognitive effort had a greater positive impact on the participants perceived sense of control than the other RAs (i.e., the non-transparent RA and low cognitive effort and transparent RA and high cognitive effort conditions) (H1b). In addition, the results showed that the participants perceived RA credibility (H1a), decision quality (H1c), and satisfaction (H1d) were positively affected by a transparent RA and were not impacted by the cognitive effort needed to access and understand the explanations of a transparent RA (i.e., low cognitive effort versus high cognitive effort). Compared to the participants' perceived decision quality, their objective decision quality was significantly higher when they were exposed to a transparent RA demanding less cognitive effort (i.e., the transparent RA and low cognitive effort condition) \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Hypothesis** & **Results** & **Estimate** & \(p\)**-Value** \\ \hline \multirow{2}{*}{Intention to adopt the RA as a decision Aid} & T2 \textgreater{} T1 & 1.0705 & 0.0001 \\ \cline{2-4}  & T3 \textgreater{} T1 & 0.9681 & 0.0002 \\ \hline \hline \end{tabular} Note: Linear regression with a random intercept model. One-tailed p-value adjusted for multiple comparison by the method of [PERSON].  
\end{table} 
Table 3: Participants’ intention to adopt the recommendation agent (RA). (H2). Furthermore, the recommendations of a transparent RA demanding more cognitive effort (i.e., the transparent RA and high cognitive effort condition) were consulted more frequently by the participants compared to the recommendations of the other conditions (i.e., the non-transparent RA and low cognitive effort and transparent RA and low cognitive effort conditions) (H3). Moreover, the explanations of a transparent RA demanding less (more) cognitive effort were consulted more frequently (H4a) and (but not) for a longer period of time (H4b) at the beginning of the participants' decision-making process, rather than at the end. When exposed to a transparent RA, the participants' intention of adopting an RA throughout their decision-making process also increased (H5). These findings contribute to filling the literature gap on RAs in organizational contexts, thus advancing knowledge in the human-computer interaction (HCI) literature. For example, past research on RAs in the online context showed that the perceived usefulness, through transparency is crucial for the adoption and continuous usage of an RA by consumers [13]. The results of this study showed that the participants' intention to adopt an RA throughout their decision-making process was significantly higher when they were exposed to a transparent RA, thus aligning with the findings of the online consumer context. In an organizational context, employees must adopt their employer's information system [44]. However, their decisions also need to be justified to their superiors [12]. Hence, this paper validates how the perceptions and usage behaviors of assortment planners are influenced by the way recommendations of an AI-based RA are presented. The results of this study provide insights for RA developers and UX designers on how to best present AI-based recommendations to employees for them to consider and adopt these recommendations. The recommendations of an AI-based RA are based on an overwhelming amount of data [33]. Consequently, based on our findings, exposing partially the logical reasoning behind the recommendations of an RA through easily accessible explanations seems to be key. Such findings can contribute to the creation of best practices in UX design. However, the way to best present these explanations is a challenge for UX designers. A condensed visual representation, rightfully balancing transparency and cognitive effort, must be created by designers [56].