Introduction

In the past, quality-of-experience (QoE) research has frequently been limited to networked multimedia applications, such as the transmission of speech, audio and video signals. In parallel, usability and user experience (UX) research addressed human–machine interaction systems and either focused on a functional (pragmatic) or aesthetic (hedonic) aspect of the experience of the user.

An aspect which has less frequently been addressed is the motivation of a user to make use of an application. The motivation is driven by the meaning (or purpose) a user associates to the usage. The meaning is, however, an important dimension to complement UX—both in terms of pragmatic and hedonic aspects—towards an integrated understanding of the driving forces for a user to actually make (long-term) use of an application. We summarize this integrated understanding in a multi-dimensional construct that we denote quality-of-user-experience (QUX).

A particular class of applications where the meaning can be expected to play a major role is the one of cyber-physical systems (CPS). Such systems, e.g. smart parking systems (e.g. [39]), learning systems utilizing guided embodiment (e.g. [40]), or multi-modal industrial machine interfaces (e.g. [70]), dispose of sensors and actuators which are able to sample and manipulate the environment they are integrated into. Thus, the interaction with them is somehow moderated through the environment. As a consequence, the environmental context can not only be considered as an influence factor (as it is common practice in QoE research, see e.g. [37]), but has to be seen as an integral part of the interaction experience. As soon as the user is involved in this environmental context, an interaction experience may take place, and thus it is important to understand the behavior of the user when engaging in an interaction, including the driving forces. Such forces might be internal user needs, as well as external (e.g. professional, educational or therapeutic) forces, which should however address the user’s internal needs in order to lead to high interaction experience, and high quality-of-life.

Another important characteristic of CPS applications is the incorporation of an associated entity such as an employer (multi-modal industrial machine interfaces) or a learning institution (learning systems) or a municipal council (smart parking) which implies consequences with regard to system usage, motivation, and QUX.

It is the aim of the present article to contribute to a better understanding of the factors that motivate system usage, and thus influence QUX. To reach this aim, we take CPS as an exemplary class of applications, and derive so-far missing aspects from the characteristics of such systems.

This article is structured as follows: After a review of related work on QoE, UX, user needs, meaning and motivation given in the “Related work” section, we propose a new multidimensional scheme to describe the quality-of-user-experience in section “From QoE and UX to QUX”. We then describe the properties of CPS and their applications in section “Cyber-physical system applications and CPS properties”, and validate the proposed scheme by applying it to prototypical CPS use cases (section “Application of the QUX concept to CPS”). Finally, we draw implications in section “Implications of QUX in the context of CPS: towards a QUX research agenda”, and conclude our article in the “Conclusions” section.

Related work

QoE: quality-of-experience

QoE research is rooted in research activities that aim to determine the impact of service characteristics on the perceptions of human users of these services. In QoE assessment, applications and services are used and evaluated by human test persons leading to quantitative results regarding their perceived overall quality, delight, and/or performance.

For a better understanding of the aims connected to the concept of QoE, the definition in the Qualinet White Paper [37] is helpful and reads as follows: “(...) the degree of delight or annoyance of the user of an application or service. It results from the fulfillment of his or her expectations with respect to the utility and/or enjoyment of the application or service in the light of the user’s personality and current state.” Although this definition already refers to certain influence factors (user’s personality and current state) it is still strongly centered towards persons which are directly interacting with the system of interest.

In order to open up this definition towards its applicability in a wider range of contexts where persons experience the quality of a system, without being a user in a strict interpretation, the authors in [54] slightly adapted this definition towards “QoE is the degree of delight or annoyance of a person whose experiencing involves an application, service, or system. It results from the person’s evaluation of the fulfillment of his or her expectations and needs with respect to the utility and/or enjoyment in the light of the person’s context, personality and current state.”. This updated definition extends the applicability of the QoE concept to applications and systems where direct interaction is not necessary to identify a person as an experiencing subject. Nevertheless, it is yet unclear which challenges such applications and systems will raise regarding QoE assessment methodologies and modeling processes.

Existing research that utilizes aforementioned definitions of the QoE concept has however still focused on rather short-term (or episodic) and media-related hedonic experiences (and only to a certain extent pragmatic aspects) to be assessed with highly homogenous and standardized assessment methodologies. Thereby, a large (data) base of quantitative results has been gathered, which allowed the community to build well established models that are able to predict QoE based on technically measurable signals or parameters, e.g. for predicting the QoE of speech communication, audio or video streaming services. However, the community did not extensively tackle long-term experiences that need to integrate the fulfillment of certain user needs that are more related towards the eudaimonic perspective(s) of positive psychology (cf. [6] and section “Psychological user needs” and “Motivation”).

UX: user experience

UX research has historically evolved from usability research which was for a long time focusing on enhancing the efficiency and effectiveness of a system [47, 52]. It was initially concerned with the prevention of negative emotions related to technology use [25]. In usability research, pragmatic aspects of analyzed (ICT) systems have been identfied as an important contributor for such preventions. However, the twist towards a modern understanding of UX focuses on the understanding of human–machine interaction as a specific emotional experience (e.g., pleasure) and considers pragmatic aspects only as enablers of positive experiences but not as contributors to positive experiences [23]. In line with this understanding, the concept of Positive or Hedonic Psychology (as introduced by Kahnemann [33]) has been embedded and adopted in HCI and UX research. As a result, the related research community has mainly focused on the hedonic aspects of experiences as described in [13] and as critically outlined by [44], in which the authors argue that this concentration on hedonic aspects has overcast the importance of eudaimonic aspects of well-being as described in positive psychology [6].

With respect to the assessment of user experiences, the devotion towards hedonic psychology goes hand in hand with the need for measuring emotional responses (or experiential qualities) [35].

In contrast to QoE, where the assessment of the experienced (media) quality of a multimedia system is in the focus, the assessment of experiential qualities in UX calls for the assessment of a range of qualities (e.g. [2, 35] list affect, emotion, fun, aesthetics, hedonic and flow as qualities that are assessed in the context of UX). Hence, this assessment approach considers a considerable broader range of quantified qualities. A seminal overview of existing evaluation methods is given in [69], where the authors identify about 96 different evaluation methods in the context of UX. The authors also state that availability of evaluation instruments is not an issue but identifying the right evaluation method for a given research problem can be quite challenging. However, the analysis in [35] comes to the conclusion that despite this large number of available measure there is nevertheless a lack of effective algorithms to enable the combinatorial integration of a (large) set of UX factors and qualities with reasonable accuracy and efficiency. In a follow-up article [36], the authors identified a widening gap between two camps of UX professionals, namely one emphasising objective measures and the other subjective accounts of experiential qualities. This widening gap has resulted in a lower number of published work from the (objective) assessment- and model-based UX research camp. Hence, large homogenous datasets that could be used for developing or training UX models based on already existing UX frameworks and related influence factors are currently not available.

In the context of the present article, we aim to integrate certain aspects of these assessment-based UX approaches in order to merge these with existing QoE approaches so as to be able to assess the subjectively perceived quality of the user experience (QUX), taking cyber-physical system applications as an example. Furthermore, the contribution of the eudaimonic dimension of system usage will be further explored with respect to its assessability.

Psychological user needs

The two preceding sections have already discussed hedonic and pragmatic aspects of a user’s experience with a system as well as the recent attention towards the eudaimonic dimension (which is strongly linked to the concept of well-being, cf. [27, 33]). A major contribution to a person’s well-being is grounded on the fulfillment of their basic psychological needs, as mentioned in [23]. Initially, the concept of need fulfillment is often connected with Maslow’s Theory of Personality [42], which describes how people satisfy various needs in the context of their work, and lists five universal needs: physical health, security, self-esteem, belongingness, and self-actualization. An extension of this need list was achieved by [57, 59]. In that context, a more particular attribution of certain needs towards motivation, e.g. to use a technological system, has been taken up by the Self-Determination Theory, however, we present a more detailed discussion on this in “Motivation” section. Based on these works, Sheldon et al. [66] have compiled a concise list of the top 10 psychological needs. Those needs are illustrated in Fig. 1.

Fig. 1
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Illustration of user needs following Sheldon [66]. Terms in italic were omitted by Hassenzahl [23]

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In the context of technological system use, an application of this concept for exploring the positive experience of interactive products, [23] has found a clear relationship between need fulfillment and positive affect towards the (technological) systems. Stimulation, relatedness, competence and popularity were especially salient needs. From these results we conclude that (psychological) needs and their fulfillment are important experience elements of subjective system perception and have to be considered in system design and evaluation. With respect to the relation of these identified needs and their fulfillment towards hedonic, pragmatic and eudaimonic aspects, existing QoE and UX literature falls short in providing clear mappings that would support proper instrumentation for evaluation purposes. In addition to these intra-personal needs, there may be a third entity or person involved in the usage of an application or service, which/who has its own needs that we will further denote as “targets”.

Meaning

The above argued assumption that need fulfillment and positive experiences are strongly interrelated can be deemed as agreed within psychology and UX research domains. However, there is a strong ongoing discussion about potentially assigning positive experiences (with technological artifacts) in user-experience research (cf. [24]), often referred to as happiness, to two distinct experience dimensions, namely hedonic and eudaimonic. In that respect, [4] argue that happiness is strongly presence (or momentary) oriented, while meaning comprises the integration of past, present and future. In a similar fashion, [27, 28] differentiate between experiences that relate to pleasure and comfort and experiences that help to create the best in oneself, and thereby meaning. This differentiation is not completely neglected in the user experience domain (to the best of our knowledge it is largely neglected in the QoE domain, with [56] being a singular exception), and work exists (cf. [23, 43]) that explicitly underpins the ability of technological artifacts to create meaning. However, explicit measurement and integration into the dyadic hedonic—pragmatic framework of positive experiences has not yet been accomplished.

Motivation

The fulfillment of psychological needs may lead to human well-being, but it explains only parts of the motivation of humans to perform certain activities, desires and needs, especially when third parties are involved that might introduce some extrinsic factors, e.g. payment in a professional work context. Theories from the field of work motivation often differentiate motivation, i.e. the reason(s) for acting in a particular way, regarding their (assumed) source of origin, into intrinsic and extrinsic motivation. Thereby, intrinsic motivation refers to activities in which the origin of the motivation is driven by an internal force that returns spontaneous satisfaction to the one performing the activity. Extrinsic motivation leads to a satisfaction that is not rooted in the activity itself, rather than in separable consequences of the activity, such as (monetary) rewards or the avoidance of punishment [64].

In a further refinement of this differentiation, the Self Determination Theory (SDT, [10]) addresses a person’s motivation to perform an activity. It distinguishes between autonomous motivation and controlled motivation. Autonomy involves “acting with a sense of volition and having the experience of choice”, whereas control refers to “acting with a sense of pressure, a sense of having to engage in the actions” [19]. Accordingly, the theory recommends that behaviors, such as system use, can be classified based on the degree of autonomous or controlled motivation. Thus, intrinsic motivation is an example of autonomous motivation, whereas extrinsic reward belongs to controlled motivation [10]. According to these theories, the type and the amount of motivation for performing an activity or using a system will then influence the performance and subjective well-being of the user.

From QoE and UX to QUX

Incorporation of the eudaimonic dimension

While existing work in QoE mainly focuses on hedonic aspects (and in UX, also on pragmatic ones), eudaimonic aspects [51, 63, 71, 73] have not been considered extensively so far in the context of UX and QoE [44, 56]. These eudaimonic aspects relate to something that is worth pursuing in life [28] or something that is intrinsically worth-while to human beings [65] and are not automatically tied to subjective experiential states.

Especially in the usage context of professional applications, the meaningfulness of system usage [60] and the growth of the user’s capabilities (=eudaimonic aspects) will certainly influence QoE and UX. In particular, professional applications must be designed as such that the user likes to continue to use the system in the long run, i.e. provide long-term acceptance (cf. [8, 22]).

Hence, in the following, we build upon the initial argumentation in [44, 56] on eudaimonic experiences and present an approach to quality-of-user-experience (QUX) as a consolidation of QoE, UX and the eudaimonic dimension.

The HEP-cube

As a first measure, we introduce the “HEP-Cube” (Hedonic–Eudaimonic–Pragmatic, cf. Fig. 2) as a simple method of qualitatively illustrating the levels of the hedonic, eudaimonic and pragmatic components of a particular application. The HEP-Cube allows for a straightforward comparison of various applications with regard to the three dimensions. While an entertainment video-streaming session may exhibit a high hedonic level, a well-designed educational application may provide high levels on all three dimensions: having fun, doing something that is meaningful to one’s life, and utilizing an easy-to-use application. In contrast, a smart parking system is mostly required to be easy-to-use. However, such a system provides a high level of meaning in the senses that it may reduce a driver’s stress and optimize the car’s route which results in reduced total traffic and pollution. Except for a gamified version of a Smart Parking system, the hedonic level of this application is considered to be low.

Note that the three dimensions are not necessarily mathematically orthogonal. Although a pie chart may be an alternative form of presenting the respective levels, the cube has the advantage of providing the—easy-to-use—possibility of illustrating ranges of levels, e.g. as clouds. This may be necessary for lots of applications as, e.g., one implementation of an application may be easy to use while another implementation may not.

Fig. 2
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The HEP-Cube provides a space in which applications may be placed according to the level of their hedonic, eudaimonic, and pragmatic aspects

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User needs and motivations in the context of QUX

Following the above introduced HEP approach for QUX it is important to understand the contribution of fulfillment of aforementioned needs (cf. “Psychological user needs” section) to these three dimensions. Therefore, we have utilized and modified the hierarchical structure of well-being factors in [20] to derive the assignment of the ten psychological user needs [66] to the hedonic, pragmatic and eudaimonic dimensions in Table 1. We considered the first five needs not pragmatic and the second set of needs pragmatic.

Table 1 User needs [66] in relation to the hedonic (hed.), pragmatic (prag.) and eudaimonic (eud.) dimensions
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Based on Huta and Ryan’s [27] concept of eudaimonia and hedonia as motivational orientations (not as experiences per se), Mekler and Hornbæk [44] reported a strong correlation of eudaimonia (e.g. “Seeking to do what you believe in” or “seeking to develop a skill”) with “Competence”, “Popularity”, “Relatedness”, “Security”, “Self-Actualization”, and “Stimulation” (significant at \(p<.001\)). All of these correlations are higher than the correlations with hedonia. At a lower significance level \((p<.05)\), they identified a correlation of hedonia (e.g. “seeking enjoyment”) with “Popularity”, “Security”, “Self-Actualization”, and “Stimulation”. The correlations for eudaimonia vs. hedonia were significantly different for “Competence”, “Popularity”, “Security”, and “Self-Actualization”. These results are incorporated in Table 1 by the star marker (“*”).

Hassenzahl et al. [26] tested the relation between need fulfillment and hedonic quality. However, in that study the eudaimonic dimension was not included.

In a similar fashion, the two types of extrinsic and intrinsic motivation can be assigned to the three HEP dimensions. Considering SDT [10], intrinsic motivation appears to be related to hedonic (fun) and eudaimonic (meaning) aspects, while extrinsic motivation is mostly related to pragmatic issues (task to be carried out). These relationships are illustrated in Table 2.

Table 2 Intrinsic and extrinsic motivation [10] in relation to the hedonic (hed.), pragmatic (prag.) and eudaimonic (eud.) dimensions
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As examples, a company provides extrinsic motivation by paying a bonus for a good task performance (pragmatic), while a worker (user) is intrinsically motivated by carrying out joyful tasks (hedonic) and by the meaning of the activity also with respect to use of the worker’s potential and competences (eudaimonic).

Both of these assignments are intended to provide a basis for initial discussions regarding the relation of needs and motivation in the context of the three HEP dimensions and for deriving a model for QUX.

HEP aspects and quality-of-user-experience

Allocating applications within the HEP-Cube does of course not determine or reveal any information on the QUX of the application in question, hence we cannot derive any respective implications.

Hence, in Fig. 3, we approach a multidimensional construct for QUX based on [22, 46]. In previous models, QoE and UX resulted from a set of hedonic and pragmatic aspects, e.g. joy-of-use and ease-of-use, respectively. We extend this model by adding the following components. First, we (vertically) add the eudaimonic dimension involving aspects such as meaningfulness and purpose-of-use, cf. [22]. Second, within the individual (HEP-)dimensions, we not only include dimension-related aspects, but also the user needs as assigned in Table 1 exerting influence on the dimension aspects.

Moreover, motivation is an additional component that moderates the impact of the user needs on the dimension aspects.

All in all, we model QUX as a result of QoE/UX, usefulness and the eudaimonic dimension, i.e. meaning and purpose of use. In section “Application of the QUX concept to CPS”, we apply this model to applications of cyber-physical systems. Section “Cyber-physical system applications and CPS properties” provides an overview on CPS applications and their properties.

Fig. 3
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QUX as a multidimensional construct involving HEP-attributes, existing QoE/UX, need fulfillment and motivation (based on [22, 46, 66] and using allocations of needs and dimension aspects from [26, 44])

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Towards a working definition of QUX

Summarizing the novelties of the QUX model illustrated in Fig. 3, we extend existing models for QoE/UX by adding the eudaimonic dimension as a factor that influences QUX, and we incorporate the user needs and motivation as factors that have an effect on the individual dimension aspects.

The work on quality-of-user-experience is in its very early stage, and experiences within the QoE community showed that coming up with a useful working definition takes a lot of research and discussions within the communities (here: QoE and UX). In this article, we provide an initial framework for QUX and invite our fellow researchers to actively partake both in terms of related research work (cf. section “Implications of QUX in the context of CPS: towards a QUX research agenda”) and discussions.

Hence, we deliberately refrain from giving a working definition.

Cyber-physical system applications and CPS properties

In this section, we first briefly describe CPS, then illustrate the variety of CPS Applications in the frame of the HEP Cube, and finally introduce general properties of CPS applications which are relevant for substantiating the QUX concept.

Cyber-physical systems

Cyber-physical systems (CPS) [1, 38, 55] can be described as a network of distributed components such as embedded systems and cloud computing entities. Individual embedded systems integrate input/output components, i.e. sensors and actuators, signal processing units, (wireless) networking interfaces, and potentially energy harvesting units instead of batteries.

In addition to the internal interconnection of system components, the performance of a CPS also depends on external information exchanged via a user interface, or via dedicated sensors and actuators with the surrounding environment in which the system is used.

CPS applications

In the following, we present selected fields of applications that illustrate the wide-spread use of CPS.

In the industrial field, CPS may not only optimize lot size 1 production, i.e. the production of a single customized item (instead of mass production), or enhance an machine operator’s work, but also ease the prediction and localization of maintenance issues and facilitate condition monitoring tasks. In logistics, CPS interfaces e.g. provide information about the warehouse stock and the location of particular entities.

Medical CPS [12] may be used permanently (pacemakers, diabetes-monitoring), on demand (ambient assisted living) or in a regular schedule (e.g. physiotherapy). Health data management allows for the provision of patient information, e.g. medical outcomes and X-ray pictures anytime, anywhere. As health data is sensitive information, the management system must provide a high level of data security.

Another field of applications is education. Museum visitors may get additional information about the exhibits, potentially displayed on mobile devices using augmented reality (AR) and dependent on their actual location within the museum. Virtual learning environments facilitate, e.g., content management and learner engagement. Similar to the museum scenario, in the tourism business, applications allow for location-based additional information on sights.

In the traffic field of applications, car drivers may be informed about the current traffic situation and use their assistance system to get to their destinations in a safe and environmentally friendly way. Smart Parking systems may allow for the easy localization of free parking spots and for easy-to-use payment of parking fees.

In entertainment business, mobile game applications such as “Pokemon Go” provide location-based gaming that utilizes a mixed-reality display.

The list of application fields and concrete applications is, of course, not complete but an illustrative selection for which QUX issues are relevant, i.e. in which users are involved. For a comprehensive overview of CPS applications, we refer to [9, 34, 67].

Fig. 4
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Characterization of (CPS) applications with regard to the HEP-Cube)

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Figure 4 depicts a small selection of CPS applications allocated within the HEP-Cube. The applications have been chosen as to represent a wide range of application fields (see above) and a wide range of HEP-component levels. While, e.g., mobile gaming is a mostly hedonic application, the aforementioned interactive learning system may exhibit high levels of hedonic (joy-of-use), eudaimonic (improvement of skills) and pragmatic (ease-of-use and utility) aspects. Some application examples involve an associated party. For instance, an industrial application and technology-supported physiotherapy are to a great extent focused on task performance, hence the level of the pragmatic dimension is high for those applications. Smart parking provides high levels in both the pragmatic and eudaimonic dimension.

Properties of CPS applications

In this section, we identify general properties of CPS applications considering the entire system appearance including the system environment. Later, we will focus on those properties which affect a user and his/her experience.

Persons and entities interested in a good QUX

The first aspect we are approaching is a rather general one: Which parties are interested in a good level of quality-of-user-experience? This question may appear to be trivial, but in the course of presenting the concept of QUX, and for the exploration of the QUX of CPS applications in particular, a look at the motivations of the involved parties appears to be useful.

An end-user may either use the system alone (single usage), together with others (co-located or via the Internet), or via some associated entity such as e.g. a company a worker is employed at (institution) or a therapist (another human user).

Three major parties may be interested in a high level of QoE of a system: The designer and producer of a particular system; the company/professional at which the system is used; and finally the end-users who actually use the system.

  • System designers or producers aim at providing an easy-to-use system that fulfills certain (intended) purposes and that is well accepted by the prospective users with feasible development and production costs. In that respect, QUX assessment can be used to improve and optimize the design of the systems beyond the mere interface also tackling the user work-flow and other user-related factors (cf. user-centered design [53]). Such an optimization should not only take place in the system development phase, but also through continuous QUX monitoring during the actual system use. The resulting system may then also be easier to market and sell.

  • Companies that deploy CPS applications in their premises are primarily interested in the pragmatic features of the applications with respect to efficient task accomplishment and a high utility of the applications. This is of special interest regarding the (possible) adaptation of the application towards individual skills of employees, which in turn enhances their work efficiency and increases their QUX with the application. However, also positive hedonic and eudaimonic experiences with the application are in their interest. Such positive experiences do not only foster mental well-being and motivation for the workers but additionally ensure high application acceptance and compliance in application usage.

  • Last, but not least, end-users are interested in CPS applications that allow them to efficiently complete their (given) tasks with pleasurable, joyful and healthy experiences.

Decision of use

In the classification of CPS applications, we used as one criterion whether the decision to use the application is entirely on the side of the end-user, or whether there is any entity involved who would moderate the use by a professional (work) relationship:

  • Professional use: In their professional work, users are potentially required to use the system for doing their job. Hence, the choice of using the system is pre-determined.

  • Private use: In their leisure time, persons may want to use an application related to their private life. Depending on their current state, e.g. motivation and fatigue, they may or may not use an application, e.g., on their tablet computer or smart phone. Then, they always have a choice of using it or not.

In section “Application of the QUX concept to CPS”, we provide three use cases of which two incorporate an associated entity, i.e. a company (employer) and a therapist, and one illustrates a simple single-user scenario.

Temporal usage structure

Within the temporal usage structure of a system or a service, we distinguish between two different temporal dimensions, the temporal duration of a single usage episode as analyzed in [18], or the temporal structure with respect to different usage episodes as described in [72]. A further influencing parameter over multiple episodes might be the system’s ability to provide stable experiences. According to [72], one can distinguish the following time spans with respect to user experiences:

  • momentary/instantaneous experience of the system characteristics as a result of the current media quality level or of events like sudden changes in transmission characteristics

  • over the retrospective appraisal of various events during an episode of usage like a call or video clip

  • the cumulative experience when evaluating a whole service after multiple episodes

According to [33] these time spans might also be attributed towards momentary-based and memory-based approaches for experience assessment. With respect to the different dimensions as discussed in section “From QoE and UX to QUX”, we assume that the full range of dimensions, especially the eudaimonic dimension, will only be assessable for multi-episodic and memorized experiences. Hence, assessment methodologies have to take care of enabling such long-term and multi-episodic assessments.

Context of use

In [37], contextual factors were defined as: Context Influence Factors are factors that embrace any situational property to describe the user’s environment. On this basis one can further distinguish [31] contextual (influence) factors into: physical, temporal, social, economic, task, and technical characteristics. All of these will exert a certain influence on the human system user. However, in the context of cyber-physical systems, the physical usage environment [3, 5] plays a particular role, as it may directly or indirectly impact the behavior of the application by means of sensor information, e.g. in case of location-based services or smart environments [7, 11, 14]. In addition, the usage environment may dedicatedly be part of the application, e.g. in augmented-reality or mixed-reality applications, and therefore plays a particular role in related experiences.

Usage consequences

Depending on the type of task an application is designed for, its use may have consequences for the user or other persons affected by its use. The consequences may be positive (e.g. improved or reinstated health, improved capabilities) or negative (threats for safety, security, or privacy). Moreover, associated entities such as a company or a therapist aim at the fulfillment of their individual targets by means of a user using a particular application.

The use of an application will unavoidably have effects on the end-user, e.g. in terms of

  • Attention and awareness [15, 32, 58]

  • Motivation (cf. “Motivation” section)

  • Effort that is required to carry out the task successfully, such as cognitive, physical, mental, perceptual and comprehension effort (cf. [32, 62])

  • (Felt) accountability/responsibility [21]

  • Fulfillment of needs (cf. “Psychological user needs” section)

  • Safety [45]

Such effects may be particularly important in, e.g., industrial systems that are operated throughout the entire work time.

Application of the QUX concept to CPS

In this section, we apply the concepts of QUX to CPS applications in scenarios which differ regarding the number and roles of entities involved. For each scenario, we provide a potential QUX model that is based on the related work (cf. Fig. 3, [22, 46]) but has, however, not yet been validated.

Scenarios

Figure 5 illustrates three exemplary scenarios.

Fig. 5
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Scenarios differing in the number and roles of entities involved: Upper panel: Involvement of a company with a professional worker; middle panel: rehabilitation scenario in which a therapist may take action according to a patient’s current state; lower panel: Single user scenario

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First, we present a professional use scenario in which the user (worker) is engaged in a long-term contract and needs to fulfill his or her tasks and duties. These contain a particular level of responsibility from both the company, i.e. providing a safe machine, and the worker, i.e. being compliant to given processes that include the system. The worker uses the application during an eight hour working day either continuously or in a sequence of usage episodes. The use environment characteristics are usually the same over time but may include significant levels of noise and temperature. Regarding the use consequences, an industrial application needs to be safe as not to imperil fellow workers. The worker usually needs to focus his or her attention to the application and his/her effort to the accomplishment of the given task(s).

The middle panel in Fig. 5 depicts a scenario in which the user is a patient who consults a, e.g. physio-, therapist. The therapist suggests the use of a particular application for a therapy that is carried out on a regular basis (e.g. episodes of 45 minutes per week). Although there may be different implementations of the same application from which the patient may choose, the general decision of use is made by the therapist. In this scenario, the associated entity (i.e. the therapist) is an integral component of the interaction loop and may directly intervene into the user’s interaction with the system. The application may be used either at the therapist’s office or at the patient’s home, thus, the environment is not necessarily pre-determined. While this kind of application usually does not affect other people, the most important user-related consequence is reinstated health and well-being of the patient.

Finally, we present a scenario that may appear trivial: Some applications may be used by a single (private or professional) user only (cf. lower panel in Fig. 5), without any external entity that takes an influence. For instance, in a private scenario such as a smart home environment, the home owner may be able to turn the lights on and off by means of gestures or voice commands or carry out easy-to-use heating control. These facilities may be fun to use, but most importantly they provide a purpose on a daily basis (eudaimonic dimension, e.g. energy-saving), comfort and a high level of pragmatic characteristics such as efficiency if they indeed are easy-to-use. The CPS application may act on its own account reacting to environmental parameters, e.g. by turning off the light automatically as soon as a person leaves the room.

While the associated entity to some extent provides for extrinsic motivation (e.g. the worker is paid a monthly wage by the company for his task performance, and a therapist may motivate a patient by giving positive feedback about her/his progress), a single user is only intrinsically motivated to use an application.

Associated entity scenario: worker

The worker scenario relates to the “Industrial Applications” given in the HEP-Cube in Fig. 4. In the following, we approach QUX in the “worker”-scenario given in Fig. 5, upper panel.

Figure 6 illustrates this scenario, in which we assume that it is the company that chooses and purchases the application which has to be used by the worker to fulfill a certain task. The company also provides the working environment (use context) for the worker, a part of which might be a compliance policy the worker has to follow. Whereas the main target of the company is to get the task done, the workers themselves mainly have other needs, such as having a fulfilling activity, having a paid job, but also feeling capable of doing it (competence).

With respect to (traditional) quality-of-experience and user experience we need to distinguish between the company and the worker. The company has mainly pragmatic views on the worker’s activity: task performance is the main (short-term) goal, and the company’s satisfaction with the worker, and the company’s satisfaction with the application, are secondary long-term goals. In turn, task performance—in terms of effectiveness and efficiency—is also a determining factor for the usability of the application from a user’s (worker’s) point-of-view; we call this sub-aspect of user experience the “ease-of-use”. Ease-of-use, together with the hedonic aspects of joy-of-use, determine the user experience, which here is the worker’s experience with the application. Considering that the application is useful for task accomplishment also from the user’s (worker’s) perspective, it may lead to the acceptance of the application for the task at hand.

Considering that the worker is in an employment contract with the company, repeated usage is to be expected, and eudaimonic aspects come to the fore. These aspects are as relevant for the company as they are to the worker. Namely, the company is interested in a meaningful activity of its workers, thus the purpose-of-use is the most important aspect. For the worker, in turn, not only the meaningfulness, but also the development of potential and skill are relevant in the long run, namely to keep the motivation and worker’s self-esteem high (which is also a secondary target for the company). These eudaimonic aspects may lead to long-term acceptance of the application (cf. [22]). Such long-term acceptance is necessary to build a lasting work relationship between company and worker, thus it directly affects the company targets.

The one who experiences the quality of the application, i.e. the quality-of-experience, is always the user of this application, hence the application’s QoE is always equal to the quality of user experience (QUX). Fig. 6 illustrates this by introducing the QUX component that not only comprises the pragmatic and hedonic aspects but also the eudaimonic dimension (cf. Fig. 3). Note that a lot of the underlying processes take place at the worker’s side, especially with regard to the connection between episodic satisfaction and eudaimonic aspects.

Application to the patient scenario

This model can also be applied to the “patient/therapist” scenario. In Fig. 7, this scenario is modeled.

While the main need/goal of the patient is physical thriving, i.e. reinstating health, the therapist’s target is to provide the patient with the right tool to rehabilitate a particular part of body in a reasonable amount of time. At the therapist’s office, the therapist instructs the patient who repeats one or more given movements, hence she is involved in the user’s interaction with the application. If the application can be used at the patient’s home, the usage of the system to a great extent depends on the patient’s motivation to use it which also depends on the appearance and QUX of the system. Even if the level of the eudaimonic dimension is high, i.e. the user considers the application meaningful and is willing to use it (high dedication), pragmatic (easy-to-use) and hedonic (joy-of-use) issues may either support its regular usage or, in the worst case, lead to poor system acceptance. This is where the therapist comes in, as she is the person who chooses the (type of) application.

One of the main differences between the “worker-” and “therapist-” model is that in the latter the associated entity, i.e. the therapist, interacts with the end-user while using the application.

Both the company and the therapist need to be interested in the application’s long-term acceptance as to support the fulfillment of their targets.

Single-user scenario

Finally, we present a single user scenario, in which the user not only has her needs but is also the entity setting the targets to be fulfilled by the use of a particular system.

As an example, a “Smart Home” scenario may include a set of equipment at the home that facilitates certain tasks of everyday life such as switching on the lights, adjusting the heating, handling automatic roller blinds, or operating the Smart TV set or the home security system. In all of these use cases, the user herself decides about the use of the system without external influence and the usage consequences are only related to the user herself and potential house mates. Smart Home tasks are mostly carried out regularly in short episodes and the system may incorporate the current situation with regard to environmental parameters such as the level of brightness or temperature.

Figure 8 provides a model for the single user scenario. As pointed out above, the user herself sets the targets towards the system. In this scenario, the resulting level of long-term acceptance is directly linked to the user, and her targets and needs, which is not the case in the third-party scenarios.

Implications of QUX in the context of CPS: towards a QUX research agenda

Addressing quality of user experience (QUX) research in a comprehensive way requires a structured course of action. Apparently, a lot of topics and aspects that we brought up in this article remain to be defined, investigated, united, tested and validated. In the following, we do not present a complete research agenda, because that would exceed the scope of this section and require an article on its own. Instead, we identify implications and main challenges that may serve as an outline for a research agenda.

In order to provide the foundation for comparable studies, a clear and universal definition of QUX is needed that covers all essential aspects of QUX and is relevant for a wide range of applications, potentially also containing associated (third) parties (e.g. companies and therapists). As we have already claimed in section “Towards a working definition of QUX”, lots of discussions and research across all related research areas and disciplines (see also below) will be necessary to further sharpen the profile of the QUX construct and to develop useful models that are empirically validated.

In the process of exploring and defining the concept of QUX in close detail, qualitative and quantitative assessment methods and methodologies need to be developed and validated that are adapted for the applications under investigation and their individual characteristics.

As far as CPS applications are concerned, the properties we presented in section “Properties of CPS applications” may serve as essential elements for the design of methods and methodologies.

First and foremost, QUX assessments of some, e.g. industrial, applications cannot be carried out under laboratory conditions but need to be performed in the field (e.g. factory hall) and the (physical) usage environment needs to be sampled comprehensively as to allow for comparable studies.

Varying temporal usage structures of various applications may have different impact on QUX, and long-term assessments need to be carried out that incorporate all three HEP-dimensions, i.e. hedonic, pragmatic and eudaimonic. Hence, the entire assessment process, including e.g. potential pre-, in situ- and post-questionnaires or appropriate, subjective and instrumental, methods of assessing QUX-related data on a regular basis, and/or interviews, and environment monitoring, needs to be carefully designed and carried out.

Moreover, the usage consequences and their effects such as awareness, (felt) accountability or safety, among others, require careful consideration.

In a multi-dimensional approach for quantitative QUX assessment, the question remains whether QUX shall—and can—be represented by a single “QUX value” or whether it shall be represented by a set of QUX factors. In a first approach, each of the three HEP-dimensions may serve as a diagnostic value for quantifying QUX. Some HEP-dimensions may also become the target values for an instrumental prediction.

Although assessment methodologies exist for all the (QUX) dimensions (only very few for the eudaimonic dimension), these methodologies are very heterogeneous and need to be unified in order to obtain comparable results across research groups.

As discussed in section “Persons and entities interested in a good QUX”, different parties are interested in a good QUX-level for different reasons. For instance, a producer of an industrial machine that provides a multi-modal user interface may want to determine the entire QUX-level of the application and be interested in potential underlying HEP-levels which may need to be adjusted during the design process (user-centered design). Thus, a close look at the factors and aspects contributing to QUX may provide significant information that allows for the production of a successful, i.e. well-designed, long-term accepted and well-used, productFootnote 1.

The HEP-Cube as a tool for illustrating the levels of the HEP-dimensions needs to be further developed and the relations of individual combinations of levels to QUX need to be investigated.

Each research community related to the quality of the user experience, e.g. QoE [37], UX [61], HCI [29], User-Centered Design (see paragraph below), Psychology (e.g. [19, 30]), Information Sciences (e.g. [41, 68]), Semiotic Engineering (e.g. [17]), etc., follows—and needs —its specific goals and approaches. However, at the end of this article, we, again, encourage all research communities to join forces and contribute to a comprehensive common understanding of quality of user experience in a trans-disciplinary approach.

For instance, the consideration of some attributes and factors influencing the QUX of CPS applications may provide a useful additional basis for the user-centered design [15, 48, 50, 53] of such applications (cf. for system designers and producers, section “Persons and entities interested in a good QUX”). As noted by Don Norman [49], “we should require machines to fill in for gaps in human performance”, and not the other way around.

Conclusions

In this article, we have added the eudaimonic dimension, i.e. the meaning or purpose of an application or service to the user, to the hedonic and pragmatic aspects that were so far considered in QoE and UX research, leading to the multidimensional construct of quality-of-user-experience (QUX).

We presented a QUX-model that involves the three HEP-dimensions (hedonic, eudaimonic and pragmatic) that are related to particular user needs. Moreover, we take the user’s motivation into account that is a moderating parameter influencing all three dimensions.

As cyber-physical system applications represent a particular class of applications in which meaning and purpose (eudaimonic aspects) are expected to play a major role, we focussed on their characteristics and applied the QUX-construct to three exemplary CPS scenarios, providing respective QUX-models that have not yet been validated.

Finally, we addressed challenges for future research on QUX in the context of CPS applications.

Fig. 6
figure 6

QUX model for CPS applications in which an associated entity (company) employs the user (worker)

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Fig. 7
figure 7

QUX model for CPS applications in which an associated entity (therapist) coaches the user (patient)

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Fig. 8
figure 8

QUX model for a single user scenario (e.g. smart home)

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