# Improving User Experience with Recommender Systems by
## 2 Theorical Background
### Hypotheses Development
#### 2.3.1 Information Transparency and Information Sufficiency  
Information transparency is an aggregate user assessment of three dimensions: clarity, disclosure, and accuracy [24]. For a recommendation message consisting of two parts of information, a problem and solution, changes in problem and solution specificity are likely to yield changes in user perceptions of the clarity, disclosure, and accuracy of the information in the recommendation message, and by extension perceived information transparency as a whole. Moreover, researchers recommend that RS designers should simplify the reading of the message by the user by using navigational efficacy, design familiarity, and attractiveness [25], which will lead to clarity and transparency [9; 25; 26]. Indeed, the content and format of the recommendations have significant and varied impacts on users' evaluations of RS [27]. Linking the latter to message characteristics, it is plausible that user perceptions of information transparency will be positively affected by (i) changing the message (text) styling by bolding key parts of the message (i.e., bolding the object being discussed); (ii) sequencing the information presentation as problem-then-solution (rather than the reverse); and (iii) communicating simple rather than complex situations. Thus, the following effects of a message's characteristics were hypothesized:  
**Hypothesis 2 (H2)**. : _Problem specificity positively impacts information transparency._  
**Hypothesis 4 (H4)**. : _Solution specificity positively impacts information transparency._  
**Hypothesis 6 (H6)**. : _Text styling positively impacts information transparency, such that styled (bold) text is associated with greater perceived information transparency than plain text._  
**Hypothesis 8 (H8)**. : _Information sequence affects information sufficiency, such that a problem-to-solution sequence positively impacts information transparency._  
**Hypothesis 10 (H10)**. : _Situational complexity negatively impacts information transparency._  
Information sufficiency refers to whether the amount of content presented to the user is enough for the user to understand the information, and in some cases to act on it [28]. By changing the degree of information specificity (i.e., problem and/or solution) and situational complexity, the amount of information available, and the way the information is conveyed to the user, user perceptions of information are likely to be augmented [20; 21; 22]. To ensure that information is clear and easy to access, which will improve information sufficiency, the information should be structured and adapted to the needs of the receivers [26; 29]. Explanations in a recommendation have an important impact on the user's behavior. Indeed, the type of explanation has a direct effect on RS use and should be different according to the desired effect [30]. For example, persuasive explanation supports the competence facet of the RS [30], while negative arguments increase the user's perceived honesty of the system regarding the recommendation [31]. Moreover, fact-based explanations (i.e., only facts with keywords) and argumentative explanations are preferred by users over full-sentence explanations [32]. The literature recommends proposing recommendations with only pertinent and cogent information [33] and excluding all information and knowledge that are not relevant for answering the request [33]. Long and strongly confident explanations can also be used to increase user acceptance [34]. Thus, choices regarding message (text) styling and information sequence may make it easier for the user to understand the presented information, and a change in information sufficiency may also be observed [25]. Thus, the following effects of a message's characteristics were hypothesized:  
**Hypothesis 1 (H1)**. : _Problem specificity positively impacts information sufficiency._  
**Hypothesis 3 (H3)**. : _Solution specificity positively impacts information sufficiency._  
**Hypothesis 5 (H5).