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Impact of Usage Behaviour on the User Experience of Netflix, Microsoft Powerpoint, Bigbluebutton and Zoom

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In order to be able to meaningfully classify the user experience and thus the popularity of products, UX questionnaires such as the UEQ, SUS or UMUX are frequently used in practice to measure the UX. This makes it possible to specifically evaluate the ratings of pragmatic and hedonic UX factors. However, it is conceivable that, in addition to users' own perceptions, external factors also have an influence on the evaluation of the UX of products. These include, for example, time or duration of use. It can be assumed that users who rate the UX of a product as good also use this product more frequently and vice versa. Such a consideration of influencing factors is particularly interesting for products that have been used frequently in recent years and thus also during the pandemic. For this reason, Netflix, Microsoft PowerPoint, Zoom and BigBlueButton were selected, which cover the range from primarily hedonic to primarily pragmatic quality. These are examined for their UX ratings as well as influencing factors.
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Impact of Usage Behaviour on the User Experience of Netflix, Microsoft Powerpoint, Bigbluebutton and Zoom
Jessica Kollmorgen1a, Martin Schrepp2b and Jörg Thomaschewski3c
1
University of Applied Sciences Lübeck, Lübeck, Germany
2
SAP SE, Walldorf, Germany
3
University of Applied Sciences Emden/Leer, Emden, Germany Keywords: User Experience, Usability, Questionnaire, UEQ-Short, UMUX-Lite, SUS, UX Measurement, UX Survey. Abstract: In order to be able to meaningfully classify the user experience and thus the popularity of products, UX questionnaires such as the UEQ, SUS or UMUX are frequently used in practice to measure the UX. This makes it possible to specifically evaluate the ratings of pragmatic and hedonic UX factors. However, it is conceivable that, in addition to users' own perceptions, external factors also have an influence on the evaluation of the UX of products. These include, for example, time or duration of use. It can be assumed that users who rate the UX of a product as good also use this product more frequently and vice versa. Such a consideration of influencing factors is particularly interesting for products that have been used frequently in recent years and thus also during the pandemic. For this reason, Netflix, Microsoft PowerPoint, Zoom and BigBlueButton were selected, which cover the range from primarily hedonic to primarily pragmatic quality. These are examined for their UX ratings as well as influencing factors.
1 INTRODUCTION In order to be able to assess how well products support their users and how satisfied they are with these products, questionnaires are commonly used. In practice, the usability and user experience of certain products can be easily measured with the help of suitable standard questionnaires such as the User Experience Questionnaire (UEQ) (Laugwitz, Schrepp & Held, 2008) or the System Usability Scale (SUS) (Brooke, 1996) in order to align them as closely as possible with the needs of users (Schrepp, 2021). However, if we look closer to the results, we often see that different users access the user experience or usability of the same product quite differently. Of course there are many reasons for such differences (Schrepp, 2021), for example personal preferences, differences in the importance of certain UX factors for the overall UX impression, or a different usage behaviour (frequency of use, experience, product used for different special tasks, etc.).
a
https://orcid.org/0000-0003-0649-3750
b
https://orcid.org/0000-0001-7855-2524
c
https://orcid.org/0000-0001-6364-5808
This in turn led to the research question of whether there are external factors that influence the perceived user experience of products in addition to the classic UX factors and that can help to explain differences in the UX evaluation. On the one hand, it is conceivable that time and the product adjustments associated with it have an influence on the evaluation of the products (von Wilamowitz-Moellendorff et al., 2007; Karapanos et al., 2008). On the other hand, however, user behaviour-dependent factors such as frequency of use may also be relevant. People who use a product more frequently typically know it better, have adjusted their usage behaviour to avoid typical UX problems of the product and therefore perceive the user experience differently. Conversely, a product is presumably only used more frequently if it offers a good user experience. In addition, the impact of such factors may also depend on the UX scale. Here a distinction between hedonic and pragmatic factors is relevant in order to obtain a suitable overall impression of the products
Kollmorgen,J.,Schrepp,M.andThomaschewski,J.ImpactofUsageBehaviourontheUserExperienceofNetflix,MicrosoftPowerpoint,BigbluebuttonandZoom.DOI:10.5220/0011380100003318InProceedingsofthe18thInternationalConferenceonWebInformationSystemsandTechnologies(WEBIST2022),pages397-406ISBN:978-989-758-613-2;ISSN:2184-3252Copyrightc2022bySCITEPRESSScienceandTechnologyPublications,Lda.Allrightsreserved397
measured (Hassenzahl, Diefenbach & Göritz, 2010). While the pragmatic qualities (PQ) are related to the ability of the product to support the user to reach concrete goals, the hedonic quality (HQ) is aimed at the fulfillment of psychological needs that do not have the sole purpose of task fulfillment, such as fun (Hassenzahl, 2008; Winter et al., 2017). It has already been demonstrated in studies that the importance of hedonic and pragmatic UX factors depend on the product category (Winter et al., 2017; Kollmorgen et al., 2021; Meiners et al., 2021). However, the usage behaviour may have a different impact of pragmatic and hedonic factors. As it is highly plausible that a high expertise with a product may cause higher ratings concerning pragmatic quality, it is quite unclear if the same effect will exist for hedonic qualities.
This led to the overarching research question, to what extent the pragmatic as well as the hedonic quality of products are influenced by the external factors mentioned above. Does the impact of these factors influence pragmatic and hedonic qualities differently? 2 UX QUESTIONNAIRES We try to evaluate the impact of demographic factors and differences in product usage behaviour on standard UX measures. Thus, we select 4 different products and evaluate them with different standardized UX questionnaires. Of course, we need to consider the time that is required by a participant to fill out multiple questionnaires and therefore we selected three widely used UX questionnaires that are relatively short: SUS, UMUX-LITE and UEQ-S. 2.1 System Usability Scale The System usability scale (SUS) (Brooke, 1996) is a short questionnaire containing 10 items that measure classical usability criteria (ease of use, usefulness, consistency, ease of learning). The items are short statements about the product. Participants can express their disagreement or agreement to these statements on a 5-point response scale. Examples for such statements are: I found the system unnecessarily complex. I felt confident using the system. The SUS is at present one of the most popular usability questionnaires. There is, in addition, a large number of research papers that investigate the psychometric properties of the SUS (Lewis, 2018). The SUS provides an overall score between 0 and 100. For half of the SUS items agreement describes a positive evaluation (see our second example item) and the answers to these items are coded as 0 to 4 from disagreement to agreement. For the other half (see our first example item) disagreement represents the positive evaluation and these items are coded as 4 to 0 from disagreement to agreement. Thus, a 4 always represents the most positive evaluation and a 0 the most negative evaluation. Per participant the scores are simply added up for all 10 items and the result (which is between 0 and 40) is then multiplied by 2.5 to scale it to a range from 0 to 100. The rescaling is done mainly to make the result easier to communicate. The SUS score for a product is then simply the average over all participant scores.
2.2 Usability Metric for User Experience (Short Form) The short form of the Usability Metric for User Experience (UMUX-LITE) (Finstad, 2010) contains just two items in the form of short statements concerning the product: This system’s capabilities meet my requirements. This system’s capabilities meet my require-ments. This system is easy to use. Participants can express their disagreement or agreement to these statements on a 7-point response scale.
The concept behind UMUX-LITE is similar to the Technology Acceptance Model (Davis, 1986) which assumes that user acceptance of a new technology is based on its perceived usefulness and perceived ease of use. The UMUX-LITE is scored like the SUS. Responses are coded as 0 to 6 from disagreement to agreement, so 0 is the most negative and 6 the most positive evaluation. The two item scores are added up per participant and the result is then divided by 12 and multiplied by 100 to transfer it to the range 0 to 100. Again, the UMUX-LITE score for a product is then the average over all participant scores. The UMUX-LITE provides a high-level measurement of overall UX. It is optimized for research situations that allow to present only a very small number of questions to the participants.
2.3 User Experience Questionnaire (Short Form) The User Experience Questionnaire (UEQ) (Laugwitz, Schrepp & Held, 2008) is designed to allow a quick assessment of UX using a number of
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task-related (pragmatic) and non-task-related (hedonic) UX aspects. It contains 26 items which are grouped into the 6 scales Attractiveness, Efficiency, Perspicuity, Dependability, Stimulation and Novelty. The item format is a semantic differential with a 7-point answer scale. The short version (Schrepp, Hinderks & Thomaschewski, 2017), called UEQ-S, contains just 8 items (4 from the pragmatic scales Efficiency, Perspicuity, Dependability and 4 from the hedonic scales Stimulation and Novelty) and is available for scenarios requiring very short completion times. This short version contains only two scales for pragmatic and hedonic quality.
Example items of the UEQ-S: inefficien
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oring o o o o o o o exciting The scale Pragmatic Quality contains the average of the first 4 items and the scale Hedonic Quality the average of the last four items. The items are scored from -3 (negative term) to +3 (positive term) and therefore this is also the range of the scales. An overall value is determined by the mean over all 8 items, it represents to overall impression concerning UX. The UEQ-S is translated in more than 30 languages. The UEQ-S questionnaire and an Excel based data analysis tool are available free of charge on https://www.ueq-online.org/.
3 STUDIES As mentioned above, the dependency between UX measurements and demographic factors or usage behaviour can depend on the UX metric used and the product being evaluated. Therefore, we investigate this dependency in our studies with different products and the three different UX questionnaires described in the last section. Four well-known products that have been heavily used in recent years are selected. The streaming platform Netflix, the video conferencing tools Zoom and BigBlueButton, and the presentation software Microsoft PowerPoint. They support leisure activities at home as well as remote working and thus a quite heterogenous set of use cases and user experience factors.
Netflix, which is mainly used for leisure, has a stronger focus on hedonic quality such as fun and visual aesthetics, while Microsoft PowerPoint (PPT) has a stronger focus on pragmatic quality and the efficient fulfillment of working tasks. The conferencing tools Zoom and BigBlueButton (BBB) cover both qualities, as they are used in both leisure and work settings. Some of these software products gained a lot of popularity and have been used much more frequently than before, which is why they are well suited for an examination of the external influencing factors.
3.1 Setup of the Studies In terms of data, the influencing factors for the four products were collected with an online survey. The survey starts with a short instruction. Then a few demographic attributes of the participant and some information about their usage behaviour are captured. We ask for: Age Gender: Male (M), Female (F) Frequency of usage (How often do you use <product name>?): Not very frequent, Several times a month, Several times a week, On a daily basis Experience (How good is your knowledge of <product name>?): Low, Medium, Strong, Excellent Duration of usage (How long have you been using <product name>?): Less than a week, Since more than a week, Since more than 6 months, Since more than a year, Since more than 5 years All questions were optional, which is why there is an additional No answer category. After this block with demographic and behavioural questions, the two items of the UMUX-LITE are shown, followed by the 8 items of the UEQ-S and then by the 10 items of the SUS. At the end of the form users can provide free textual comments concerning strength and weak-nesses of the product. 3.2 Study Implementation Participants for the studies were recruited via different universities as well as over a panel and received some monetary compensation for their participation in the study. The questionnaires were distributed to different target groups each, but overlaps cannot be excluded. The received either German or English questionnaires in the period from September to December 2021. After the collection, the data were cleaned to increase their quality. In the process, data records were removed if they had too short a processing time or too few clicks, or if the quality assurance question was answered incorrectly.
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Therefore, a total of 97 records were removed and a total of 338 remain. The average age of the participants was about 28 years. More detailed descriptions can be found in the Research Protocol (Kollmorgen et al., 2022). 3.3 Impact of Gender First, we investigate if gender has an impact on the ratings of SUS, UMUX-LITE or UEQ-S for the four products. Overall, only one person classified itself as divers, and a small number of participants choose the No answer option, which is why no meaningful results could be derived for these categories. Therefore, we concentrate on the differences between male and female participants. The percentage of male and female participants for the studies is shown in Table 1 below.
Table 1: Distribution of male and female participants. Gender Netflix N=97 PPT N=89 Zoom N=76 BBB N=76 Male 55 % 74 % 50 % 54 % Female 43 % 26 % 47 % 45 % Table 2 shows the values of the three UX questionnaires depending on gender. For the UEQ-S we use the overall value, i.e. ignore for the moment pragmatic and hedonic qualities.
Table 2: Impact of gender on the 3 UX scales. Range 0-100 for UMUX-LITE and SUS, from -3 to +3 for UEQ-S. Quest. Gen Netf. PPT Zoom BBB UMUX-LITE M 81.90 72.22 75.66 66.87 F 80.20 72.46 82.64 68.38 SUS M 84.40 69.62 73.36 69.82 F 81.90 73.70 82.64 70.81 UEQ-S M 1.08 0.20 0.73 0.26 F 1.00 0.41 1.07 0.58 Gender had only for Zoom a significant influence on all three questionnaires (p < .05, t-test, two-sided). Female participants tend to rate Zoom better than male participants. This is true for the scores of all three UX questionnaires and is therefore not just a random effect. For the other products, there was no significant influence of gender on the scores. The difference in the ratings of Zoom and BBB is quite interesting. Both products belong to the same product category and support similar use cases. But Zoom is rated much higher by females than by males in all three UX scales, while such an effect cannot be observed for BBB. A possible explanation is perhaps that BBB is mainly used in an educational context, while Zoom is a general video conferencing tool that is used professionally and for private communication. The UEQ-S scores depending on gender are shown in Figure 1. Figure 1: Impact of Gender on the UEQ-S scores. Range from -3 to +3. As can be seen, there are only small differences between the gender ratings. This difference is only significant for Zoom, but there is a slight tendency that female participants give higher ratings, except for Netflix (this is also true for the other two questionnaires). Therefore, due to our medium sample sizes, we cannot rule out that there is no effect of gender on the ratings, but in each case the effect is quite small. 3.4 Impact of Usage Frequency The usage frequency can also have an influence on the perception and evaluation of the UX. On the one hand, the more frequently users actively engage with the product of the categories considered, the more features or advantages and disadvantages they can identify. On the other hand, they also adjust their behaviour to avoid known usability problems, which may be forgotten already when they evaluate the product. The distribution of usage frequency on the ratings is shown in Table 3. The percentage distribution for Zoom, for example, is already determined by the type of product (target group student). 00,511,522,53NetflixPPTZoomBBB
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MaleFemale
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Table 3: Distribution of usage frequency. Usage Frequency Netflix N=97 PPT N=89 Zoom N=76 BBB N=76 Not very freq. 9% 58% 25% 41% Sev. Times month 36% 31% 33% 29% Sev. Times week 38% 8% 32% 28% Daily basis 16% 2% 4% 3% The usage frequency is also examined in Table 4, again showing the values of the three questionnaires. Table 4: Impact of usage frequency. Range 0-100 for UMUX-LITE, and SUS; from -3 to +3 for UEQ-S. Frequency Netflix PPT Zoom BBB UMUX-LITE Not very freq. 74.07 70.07 75.44 66.15 Sev. times month 79.29 72.02 78.67 73.75 Sev. times week 83.78 82.14 83.68 75.69 Daily basis 80.21 83.34 88.89 83.33 SUS Not very freq. 70.28 69.02 72.63 70.70 Sev. times month 79.50 71.96 77.50 73.50 Sev. times week 87.16 75.36 82.92 72.50 Daily basis 87.50 80.00 88.33 90.00 UEQ-S Not very freq. -1.88 0.18 0.68 0.35 Sev. times month 0.95 0.26 1.08 0.62 Sev. times week 1.20 0.54 0.82 0.69 Daily basis 1.38 0.81 1.54 1.00 As we can see, the more frequently a product of these categories is used, the better is the UX judgement in the questionnaires. Thus, we have a clear effect in this case. This is not unexpected. If a product shows good UX it will be used more frequently. Conversely, over time the more frequent users will be the ones with a better impression. Figure 2 shows the SUS scores for the four investigated products in dependency to the self-reported usage frequency. Many of the differences are relatively high, i.e., the impact on usage frequency on the scale scores leads to meaningful differences. An ANOVA shows that the frequency of usage had a significant impact (p > .05) on the SUS scores for Netflix and Zoom, on the UMUX-LITE scores for Zoom and BBB, and for the UEQ-S score for Netflix and BBB. The data of the SUS are shown in Figure 2. Once again, it is clear that Netflix and Zoom overall are rated better than PPT and BBB in all categories of usage frequency. It is an interesting observation that the ratings of all 4 products are nearly the same by users who use the product not very frequent. Of course, we must be a bit careful with conclusions, since the values in some usage categories are based on only a few data points. Figure 2: Impact of usage frequency on SUS scores. Range 0-100. As the data also show, the UEQ-S ratings vary significantly depending on the usage frequency. Users who deal with the respective product on a daily basis rate it best by far. Those who do not use it frequently rate it the worst. This is clear in the case of Netflix: it is the only category which is rated below 0. Only Microsoft PowerPoint does not show any significant impact on UX metrics. This could be due to the uniqueness of the product, as pupils and students are often only recommended PPT and there is little experience with other presentation tools. However, it is clear that usage frequency impacts product UX ratings, which is visible in Figure 3. Figure 3: Impact of usage frequency on UMUX-LITE scores. Range 0-100. 020406080100NetflixPPTZoomBBB
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Not very frequentSeveral times a monthSeveral times a weekOn a daily basis020406080100NetflixPPTZoomBBB
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3.5 Impact of Knowledge It can also be assumed that the knowledge of the range of products could have an influence on the evaluation. Similar to the higher frequency of use, the advantages and disadvantages also become clearer with better knowledge of the products. The distribution of the self-reported knowledge is shown in Table 5. Table 5: Distribution of self-reported product knowledge. Know-ledge Netflix N=97 PPT N=89 Zoom N=76 BBB N=76 Low 7 % 9 % 20 % 25 % Medium 22 % 51 % 41 % 45 % High 54 % 35 % 34 % 20 % Excellent 19 % 6 % 5 % 1 % Table 6 shows the UX ratings of the three questionnaires depending on the stated knowledge. Table 6: Distribution of self-reported product knowledge. Range 0-100 for UMUX-LITE, and SUS; from -3 to +3 for UEQ-S. Knowledge Netflix PPT Zoom BBB UMUX-LITE Low 75.00 66.63 67.78 61.84 Medium 78.97 68.15 76.61 73.04 High 79.65 77.69 83.33 76.67 Excellent 87.50 86.67 95.84 83.33 SUS Low 77.08 63.12 68.33 66.32 Medium 77.74 68.56 74.84 73.01 High 82.36 74.03 82.98 77.67 Excellent 92.36 81.00 91.25 80.00 UEQ-S Low 0.27 0.22 0.40 0.36 Medium 0.99 0.02 0.79 0.46 High 0.97 0.56 1.10 0.67 Excellent 1.43 0.53 1.12 0.50 As in the previous observations, it is clear that Netflix and Zoom are rated better overall. Furthermore, the previous assumption is confirmed once again: the better the participants rate their knowledge of the respective product, the better they also rate the product itself on average. At least there is a clear trend visible for all three questionnaires. This is also shown graphically for the UEQ-S ratings in Figure 4. Figure 4: Impact of knowledge on the UEQ-S scores. Range from -3 to +3. A variance analysis (ANOVA) reveals that there is only for BBB a significant influence of knowledge on the ratings at the 5% level. This can be due to the fact that the effect size is relatively small, and our sample size therefore does not allow to detect a significant effect. That is why we can state that there is at least a trend visible, but no significant effect. 3.6 Impact of Duration of Use It can be assumed that users who have been using a product of these categories for a long time also know it better. This does not mean that they know all functions and can operate it perfectly, but that they are able to find their way around the product according to their needs. Vice versa, users who have been using a product for a short time may not know how to reach their goal. It is necessary to investigate what influence the duration of Use has on the ratings. Table 7 shows the distribution of the participants over the categories. This distribution is different for the products, so a comparison of the impact is hardly possible. In addition, since only a few participants have been using the products for less than a year, these were combined into the "Shorter" category. Since no person has used BBB for longer than 5 years, no relevant statement can be made here. 00,511,522,53NetflixPPTZoomBBB
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LowMediumHighExcellent
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Table 7: Impact of duration of use. Duration of Use Netflix N=97 PPT N=89 Zoom N=76 BBB N=76 Shorter 2 % 1 % 8 % 39 % More than a yea
r
64 % 10 % 88 % 55 % More than 5 years 33 % 88 % 3 % Table 8 shows the ratings of the three different UX metrics. Table 8: Influence of the duration of use on the UX ratings. Range 0-100 for UMUX-LITE, and SUS; from -3 to +3 for UEQ-S. Knowledge Netflix PPT Zoom BBB UMUX-LITE Shorter 70.84 33.33 85.42 33.33 More than a year 81.18 81.48 78.86 78.17 More than 5 years 80.47 71.79 83.34 SUS Shorter 82.50 27.50 84.38 53.12 More than a year 82.54 75.28 77.87 76.55 More than 5 years 84.06 70.77 67.50 UEQ-S Shorter 0.19 -1.00 2.03 -1.06 More than a year 1.06 0.76 0.78 0.60 More than 5 years 1.00 0.23 1.50 In contrast to the frequency of use and the knowledge of the product, we can see no clear trend here, as shown in Figure 5. Figure 5: Impact of duration of use on the UEQ-S scores. Range from -3 to +3. On the one hand, this is due to the fact that the “Shorter” category only contains a small amount of data, which means that this cannot be clearly interpreted. On the other hand, the other categories also have a different number of respondents depending on the product, which is why the results are unstable. For this reason, further interpretations of the data should be refrained from. Despite the assumption, it is not clear whether the duration of use has an influence on the evaluation of the UX of the products. 3.7 Evaluation of Influencing Factors Gender has, with the exception of one product, no significant influence on the scores of the UX scales. As expected, however, the data from our study show that influences by usage frequency, and knowledge are likely. The usage frequency has been proven to be the most relevant influencing factor. Here we found some effects that proved to be significant even with moderate sample sizes. Although in most cases no significant influences could be demonstrated for the other two factors, which can be due to the small sample size and the unequal distribution of the respondents over the existing categories, there was at least a trend in the data visible. 4 IMPACT ON HEDONIC AND PRAGMATIC QUALITY The assumption, which has already become visible to some extent in the previous sections, is that users have different demands on the user experience of the products depending on the use case. It can be assumed that for products such as PPT, which are used for work purposes, the focus is particularly on the fulfilment of pragmatic goals. As part of the user experience, these also coincide with the demands on usability. Furthermore, in the case of products that are primarily intended for private use, such as Netflix, hedonic factors like fun or beauty should not be neglected (Hassenzahl, 2001). These products are used voluntarily in the free time and are rarely predefined by other people such as employers. This can be seen, for example, when looking at the knowledge of Netflix. About one fifth of all respondents said they had excellent knowledge about this product and also rated it high. However, it is unclear, for example, how the pragmatic and hedonic quality for Zoom is perceived, -3-2-10123NetflixPPTZoomBBB
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since this tool is also used for private video calls in addition to work purposes. In the following, we will therefore examine how users perceived the pragmatic and hedonic quality of the four products. As already explained, usability questionnaires such as SUS or UMUX primarily measure usability and therefore pragmatic quality. For the four products Netflix, PPT, Zoom and BBB, it is therefore interesting to consider how other questionnaires besides the UEQ classify pragmatic quality and whether this is perceived similarly across questionnaires. Table 9 evaluates the scale values for the four products in terms of usability and pragmatic quality as well as hedonic quality. The first four items of the UEQ-S were considered for the PQ, the last four items for HQ. The UEQ-S ratings were also converted into percentages to enable better comparability with the scale values of the SUS and UMUX-LITE, which lie between 0 and 100. According to simple percentage calculation, the values were first scaled to 0-6, and then multiplied by 100 and divided by 6. As the scale values show, Netflix was rated best overall, followed by Zoom. Only with regard to the UEQ-S and its evaluation of pragmatic quality in specific, Zoom was rated best. BBB and PPT are not rated well but are still rated in the midfield. In the Video Conference Tool product category, Zoom is rated significantly better (p > .05) than BBB on average. The reason given by 8 out of 19 open responses is that some functions (e.g. volume control of users) are missing. It can be assumed here that Microsoft PowerPoint is not seen as simple enough to achieve goals due to its complex functionality. The many different functions according to 21 out of a total of 37 open Table 9: Scale values. Range 0-100. The UEQ-S scores were converted for better comparability. Product Netflix PPT Zoom BBB UMUX-LITE 80.67 72.28 77.85 67.54 SUS 82.89 70.67 76.81 70.36 UEQ-S 67.00 54.17 64.00 56.67 UEQ-S PQ Scale 70.17 66.33 75.17 68.17 UEQ-S HQ Scale 63.67 42.00 52.83 45.17 responses to the survey on PPT are too extensive, complicated or not logical, such as creating your own slide designs. This is consistent with the observations made in the previous sections. All four products fundamentally meet the needs of users in achieving their goal. Netflix and Zoom show a better usability through simpler and more complete functions. This is also shown when comparing the UMUX-LITE and SUS values with the PQ Scale of the UEQ-S (see Table 9). The values show only minor differences. It seems that the pragmatic quality measured with the UEQ-S is strongly related to the values of the SUS and UMUX. In terms of hedonic quality, it is again clear that Netflix is rated also best of all four products. As already explained, hedonic quality is particularly relevant for products that are used for leisure activities. Thus, all products are overall rated bad in their hedonic quality. This is also a typical effect. In terms of HQ, the UEQ-S roughly asks how much fun the product is and how original it is. However, since all four products studied have been on the market and used for some time, they are classified as less orig inal. For this reason, revisions to the design are often used in practice. This is one reason why the HQ scores significantly worse in a direct comparison with the PQ. This can also be seen in the following Figure 6. In Section 3 we showed that usage frequency has a clear influence on product ratings. For this reason, this external influencing factor is once again considered specifically in relation to pragmatic and hedonic quality, which is the purpose of Figure 6. As the Figure 6 shows, similar to the observation of the overall UEQ-S ratings, a trend can be seen specifically for pragmatic quality. This trend could also be demonstrated for Netflix and Zoom in the ANOVAs (p > .05). Netflix's Hedonic Quality rating is again in line with expectations: Users who use the product more often rate hedonic quality higher and vice versa. However, the situation is different for the other three products. No clear trend is discernible for them. This is also shown in the ANOVAs, because only for Netflix was an impact of the usage frequency for the hedonic quality at the 5% level proven. Overall, nevertheless, all reviews of the products are poor in terms of hedonic quality. For PowerPoint, the ratings are in the negative range regardless of the frequency of use. In summary, it is clear that the UEQ-S can be clearly distinguished into PQ and HQ. While all three questionnaires found similar values for the PQ, no clear trend is discernible for the HQ. As can also be seen from the Research Protocol (Kollmorgen et al., 2022), similar results are obtained for the other external influencing factors presented.
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Figure 6: Impact of usage frequency on UEQ-S, PQ Scale and HQ Scale. Range from -3 to +3. 5 CONCLUSIONS Finally, the general results and conclusions of our studies will be assessed. It is clear that Netflix is rated best overall concerning UX, regardless of the questionnaires considered. Zoom is clearly rated lower as Netflix, but still higher than BBB and PPT, which show relatively similar ratings (see Table 9). The difference of Zoom and BBB is quite interesting. Both products support similar use cases, but the focus of BBB is more to support education in universities, while Zoom is also used often for private video conferences. This was also relevant in Pandemic, when remote video calls replaced in person events due to lockdowns. BBB, on the other hand, is often a mandatory software depending on the university and employer. Nevertheless, BBB contained only a few participants who are very experienced in using the product, even though it has been on the market longer than its competitor Zoom. This is maybe an explanation why especially the rating of the hedonic quality of Zoom is much higher that the corresponding rating of BBB. Microsoft PowerPoint as a tool to create efficient presentations in business and in educational settings has of course a focus on pragmatic quality. Concerning the UEQ-S we see that the rating concerning PQ is not bad, but the rating concerning HQ is not satisfying. Of course, PPT is a much more complex product than the three other investigated products. This is also reflected in the observation that most users (87.64%) have been using PPT for more than 5 years, but still only a few rated their knowledge as excellent (5.62%). So, the high complexity of this product is maybe the force behind the relatively low HQ and medium PQ rating. In terms of influencing factors, gender was initially found to have no significant effect on the UX ratings. The usage frequency showed a significant influence on the respondents' perceived usability but not so much on the hedonic quality for all products. Self-reported product knowledge also showed an impact on the usability related scores (UMUX-LITE, SUS, PQ), but not on hedonic quality. The duration of use seems to have not a big impact on the ratings, but here the products differ with respect of the average duration of use and thus some categories contained not much data. Overall, the article can be seen as a methodological example of how influencing factors can be considered in usability research and future work on this would be worth looking at. In summary, all products used in the study exhibit acceptable ratings concerning pragmatic quality. -3-2-10123NetflixPPTZoomBBB
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Scoring of the product
on Hedonic QualityNot very frequentSeveral times a monthSeveral times a weekOn a daily basis
ImpactofUsageBehaviourontheUserExperienceofNetflix,MicrosoftPowerpoint,BigbluebuttonandZoom405
However, the situation is different with the hedonic quality. Netflix also showed reasonable ratings concerning hedonic quality, which is of course important for a product mainly used for fun and leisure activities. The other three products scored clearly worse concerning hedonic quality. These products are of course more task-related, i.e. their design goals are of course more related to the pragmatic quality or usability. The studies also showed that the used measurement instrument is important to draw the right conclusions from results. If hedonic quality is an important success factor for a product it is important to measure this with a dedicated scale. If you use a purely usability centric method like SUS or UMUX-LITE, differences in hedonic quality are invisible in your results. Finally, some limitations of our studies must be mentioned. First, the available number of respondents was relatively low in our studies. This is especially problematic, since these respondents did not distribute equally over all categories of the investigated influencing factors, so some results are based on only a small number of responses. Of course, the results should be confirmed with a wider range of products as well. REFERENCES Brooke, J. (1996). SUS-A quick and dirty usability scale. In Jordan, P., Thomas, B. (Ed.). Usability Evaluation in Industry, 189(194). London: Taylor & Francis. pp. 4-7. Davis, F. (1986). A technology acceptance model for empirically testing new end-user information systems - Theory and results. PhD Thesis, Massachusetts Inst. of Technology. Finstad, K. (2010). The Usability Metric for User Experience. In Interacting with Computers 22(5). pp. 323-327. DOI 10.1016/j.intcom.2010.04.004 Hassenzahl, M. (2001). The Effect of Perceived Hedonic Quality on Product Appealingness. In International Journal of Human-Computer Interaction 13(4). pp. 481-499. DOI 10.1207/S15327590IJHC1304_07 Hassenzahl, M. (2008): Towards an experiential perspective on product quality. In Proceedings of the 20th International Conference of the Association Francophone d'Interaction Homme-Machine on - IHM '08, Metz, France: Association for Computing Machinery. pp. 11-15. DOI 10.1145/1512714.1512717 Hassenzahl, M., Diefenbach, S., Göritz, A. (2010): Needs, affect, and interactive products - Facets of user experience. Interacting with Computers 22(5). pp. 353-362. DOI 10.1016/j.intcom.2010.04.002 Karapanos, E., Hassenzahl, M., Martens, J.-B. (2008). User experience over time. In CHI EA ’08 26th Annual ACM Conference on Human Factors in Computing Systems. Florency, Italy: Association for Computing Machinery, Inc. pp. 3561-3566. DOI 10.1145/1358628.1358891 Kollmorgen, J., Meiners, A.-L., Schrepp, M. & Thomaschewski, J. (2021). Ermittlung relevanter UX-Faktoren je Produktkategorie für den UEQ+. In Wienrich, C., Wintersberger, P. and Weyers, B. (Ed.). Mensch und Computer 2021 - Workshopband. Bonn: Gesellschaft für Informatik e.V. DOI 10.18420/muc2021-mci-ws01-362 Kollmorgen, J., Schrepp, M., Thomaschewski, J. (2022). Protocol for A Comparison of three short User Experience Questionnaires. DOI 10.13140/RG.2.2.32773.01760 Laugwitz, B., Schrepp, M., Held, T. (2008). Construction and evaluation of a user experience questionnaire. In Holzinger, A. (Ed.). USAB 2008, LNCS 5298. pp. 63-76. DOI 10.1007/978-3-540-89350-9_6 Lewis, J. R. (2018). The System Usability Scale: Past, Present, and Future. In International Journal of Human–Computer Interaction 34(7). pp. 577-590. DOI https://doi.org/10.1080/10447318.2018.1455307 Meiners, A.-L., Kollmorgen, J., Schrepp, M., Thomaschewski, J. (2021). Which UX Aspects Are Important for a Software Product? In Schneegass, S., Pfleging, B. and Kern, D. (Ed.). Mensch und Computer 2021. MuC '21: Mensch und Computer 2021. Ingolstadt Germany, 05 09 2021 08 09 2021. New York, NY, USA: ACM. pp. 136–139. DOI 10.1145/3473856.3473997 Schrepp, M., Hinderks, A., & Thomaschewski, J. (2017). Design and evaluation of a short version of the user experience questionnaire (UEQ-S). In International Journal of Interactive Multimedia and Artificial Intelligence 4 (6). pp. 103-108. DOI 10.9781/ijimai.2017.09.001 Schrepp, M., Thomaschewski, J. (2019). Design and Validation of a Framework for the Creation of User Experience Questionnaires. In International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 5, No. 7. pp. 88-95. DOI 10.9781/ijimai.2019.06.006 Schrepp, M. (2021). User Experience Questionnaires: How to use questionnaires to measure the user experience of your products? KDP, ISBN-13: 979-8736459766. von Wilamowitz-Moellendorff, M., Hassenzahl, M., Platz, A. (2007). Veränderung in der Wahrnehmung und Bewertung interaktiver Produkte. In Gross, T. (Ed.). Mensch & Computer 2007: Interaktion im Plural. München: Oldenbourg Verlag. pp. 49-58. Retrieved from https://dl.gi.de/handle/20.500.12116/7273;jsessi onid=C644DF5B586213C455E74EC0A4D4B835 Winter, D., Hinderks, A., Schrepp, M., Thomaschewski, J. (2017). Welche UX-Faktoren sind für mein Produkt wichtig? In Hess, S. and Fischer, H. (Ed.). Mensch und Computer 2017 – Usability Professionals, Regensburg: Gesellschaft für Informatik e.V. pp. 191-200. DOI 10.18420/muc2017-up-0002
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Die User Experience ist ein relevanter Aspekt für eine erfolgreiche Produktentwicklung. Ein geeignetes Instrument für die quantitative Messung der User Experience sind Fragebögen wie der UEQ+. Dieser erlaubt es, mithilfe der zur Verfügung gestellten Skalen produktindividuelle Fragebögen zu erstellen. Es ist jedoch wahrnehmbar, dass manche UX-Faktoren für konkrete Produktkategorien relevanter sind als für andere. Welche Faktoren in welchem konkreten Anwendungsfall wichtig sind, wird in dieser Arbeit gezeigt. Dafür wurden zwei Studien aus 2016 und 2017 ausgewertet. Durch eine Korrelationsanalyse sowie t-Tests konnte nachgewiesen werden, dass die Ergebnisse beider Studien robust genug sind, sodass sie zu einem Gesamtdatensatz zusammengefasst werden konnten. Aus diesem Datensatz konnte eine globale Relevanzgrenze ermittelt werden, bei deren Überschreitung ein Faktor als relevant für ein Produkt angesehen werden kann. Das Ergebnis zeigt, dass die vermuteten Wichtigkeitsunterschiede nachgewiesen werden konnten. Dies sollte in der Produktentwicklung berücksichtigt werden, u. a. um die Stärken und Schwächen des Produkts zu identifizieren.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 1986. Includes bibliographical references (leaves 233-250). Photocopy.
Book
A good user experience is extremely important for the success of an interactive product. It is therefore important for the design and improvement of the product to be able to measure this aspect. Different users often have strongly diverging opinions about the user experience of a product. Because questionnaires allow data to be collected from large samples with little effort, they are a very popular and widely used method for quantifying the user experience.This book is intended to help user experience researchers to use questionnaires in their research activities and to get the best out of the data. The book provides an overview of popular questionnaires and describes their basic concepts and structure. To help researchers to select the best questionnaire for their projects different common user experience qualities are discussed in detail. It is also described how to create new questionnaires that measure the relevant aspects of user experience. Specific guidance on data collection, data analysis, and presentation of results is also provided.
Article
The System Usability Scale (SUS) is the most widely used standardized questionnaire for the assessment of perceived usability. This review of the SUS covers its early history from inception in the 1980s through recent research and its future prospects. From relatively inauspicious beginnings, when its originator described it as a “quick and dirty usability scale,” it has proven to be quick but not “dirty.” It is likely that the SUS will continue to be a popular measurement of perceived usability for the foreseeable future. When researchers and practitioners need a measure of perceived usability, they should strongly consider using the SUS.
The Usability Metric for User Experience
  • K Finstad
Finstad, K. (2010). The Usability Metric for User Experience. In Interacting with Computers 22(5). pp. 323-327. DOI 10.1016/j.intcom.2010.04.004
The Effect of Perceived Hedonic Quality on Product Appealingness
  • M Hassenzahl
Hassenzahl, M. (2001). The Effect of Perceived Hedonic Quality on Product Appealingness. In International Journal of Human-Computer Interaction 13(4). pp. 481-499. DOI 10.1207/S15327590IJHC1304_07
Towards an experiential perspective on product quality
  • M Hassenzahl
Hassenzahl, M. (2008): Towards an experiential perspective on product quality. In Proceedings of the 20th International Conference of the Association Francophone d'Interaction Homme-Machine on -IHM '08, Metz, France: Association for Computing Machinery. pp. 11-15. DOI 10.1145/1512714.1512717
Needs, affect, and interactive products -Facets of user experience
  • M Hassenzahl
  • S Diefenbach
  • A Göritz
Hassenzahl, M., Diefenbach, S., Göritz, A. (2010): Needs, affect, and interactive products -Facets of user experience. Interacting with Computers 22(5). pp. 353-362. DOI 10.1016/j.intcom.2010.04.002