Keywords

1 Introduction

User Experience (UX) has become an important new focus for both practitioners in interaction design and researchers in the evaluation of Human Computer Interaction [18]. UX is defined as users’ emotions, beliefs, preferences, perceptions, physical and psychological responses, behaviors and accomplishments that occur before, during and after use of a device (ISO 9241-210:2010). Thus, UX includes user experience before actual device usage. Factors impacting user experience before the actual use, such as installation of the product, are known to impact the perceptions and attitudes toward a digital product or service [17].

It is thus important to understand how users experience this initial interaction with the product and possibly identify the factors that influence a successful product installation. In addition, it has been shown that an unpleasant first experience can have negative consequences for the user’s experience and perceptions of the brand [6].

This paper aims to empirically test factors that may explain a successful technology product installation. To this end, we use a controlled laboratory environment to investigate how users’ perceptions, emotional and cognitive states, and behaviors influence successful product installation.

2 Hypotheses : Factors Influencing Successful Electronic Equipment Setup

2.1 Attitudinal Factors

This study specifically focuses on two attitudinal factors that can potentially impact the performance of an installation: User motivation and self-efficacy. There are two main types of motivation : intrinsic and extrinsic [31]. Deci and Ryan [28] define extrinsic motivation as achieving a specific goal or reward. Intrinsic motivation is more related to a personal goal and a perception of pleasure [31]. Booth [4] suggests that with a high degree of motivation, people spend more effort in overcoming problems. Thus, a (intrinsically or extrinsically) motivated user should be more successful at setting up an electronic device. Thus, we posit a first hypothesis.

  • H1 : A user’s motivation has a positive impact on installation success.

Self-efficacy is defined as people’s beliefs and personal judgment about their abilities to perform different types of actions [2]. Self-efficacy plays a key role in the probability to accomplish different tasks and achieve goals. People who are reported high in self-efficacy think they have the capacity to succeed in a specific task [32]. Moreover, Bandura [3] suggests that people who believe they are self-efficient at performing a task will produce the necessary efforts to succeed. Because human motivation is generated cognitively and directly influences the user’s self-efficacy, a high self-efficacy level plays an important role, especially when an individual has to face difficulties and obstacles.

  • H2 : A user’s perceived self-efficacy has a positive impact on installation success.

2.2 State Factors

Concerning user state factors that can influence performance, we focused on arousal, cognitive engagement, and valence. Arousal is defined as general psychological and physiological activation. Thus, a user can move from a calm state to an excited state. Stress is defined as a state of physiological activation and arousal when people think they don’t have the capacities to deal with threats or pressure [29]. Nixon [1] suggests a curvilinear relationship between stress and performance. Many researchers investigated the inverted-U relationship [9, 10, 12, 22] between arousal and performance. Until the inflexion point, an increase in arousal has a positive impact on performance, but passed this point, an increase in arousal has a negative impact on performance [23]. In a lab context where users are monitored, we expect that they may pass the inflexion point and observe that greater arousal leads to less successful installation. Thus, we posit the following hypothesis.

  • H3 : A user’s arousal has a negative impact on installation success.

Blumenfeld and Paris [14] define cognitive engagement as the willingness to pursue efforts to achieve goals and comprehend complex ideas. In order to enhance the usability of interfaces and design new systems, cognitive engagement is essential to analyse the user’s performance and reactions [21]. Greene et al. [16] and Charland et al. [8] show that cognitive engagement is tied to academic performance. In order to achieve goals such as an installation, cognitive and metacognitive strategies are necessary [14]. Metacognitive strategies are related to setting, planning goals when performing a task. Thus, cognitive engagement would be a useful factor in order to employ the best strategies to install the new electronic device.

  • H4 : A user’s cognitive engagement has a positive impact on installation success.

Emotional valence is defined as the intensity of an emotion, positively or negatively [15] Emotional valence can be useful in order to understand performance during the installation. For example, it has been shown that pleasure and positive interactions with a product result when the activities or tasks are easily performed [13]. Moreover, emotion is directly related to the outcome. There is a sense of accomplishment that results for people when a goal is achieved and emotions help to evaluate this experience [13]. Thus, we posit a positive relationship between emotional valence and installation success.

  • H5 : A user’s positive emotional valence has a positive impact on installation success.

2.3 Behaviors

Finally, we investigate the relationship between a specific behavior, reading installation instructions, and performance. On the one hand, research suggests a positive relationship between reading instructions and performance [20]. On the other hand, research suggests that users are generally not inclined to read instructions ([7, 24] especially for product that are perceive as easy to use [33]. Thus, we posit our final hypothesis.

  • H6 : Reading the installation instructions has a positive impact on installation success.

These hypotheses are depicted in Fig. 1 below.

Fig. 1.
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Research model

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3 Research Method

3.1 Design, Sample, and Procedure

We conducted a lab experiment with 29 participants (17 male, 12 female) between 20 and 70 years old with diverse backgrounds in terms of skills and motivation with regards to self-installation. In an experimental living room, each participant had to unbox a new entertainment electronic device, uninstall the old equipment and install the new device. Participants were provided with a short printed guide instructing them how to use a tablet on which they could access a step-by-step instruction mobile application. They were free to conduct the task in whichever order they preferred. Consequently, the steps taken by participants did not all follow a linear pattern. The experiment ended when the participant believed to have completed the electronic device installation successfully. The study was approved by the ethics committee of our institution and each participant received a gift card as a compensation.

3.2 Experimental Setup and Stimuli

We deployed three cameras around the task area in order to ensure that every manipulation done by the user was recorded. Those cameras not only enabled us to observe the participant’s reactions at every step of the experience, but also to observe all the actions that could be reported in synchronization with the other tools, in order to determine which specific moments were associated with varying levels of arousal and cognitive engagement. Synchronization was done based on Léger et al. [19] guidelines. We also strapped a GoPro camera on the user’s chest to observe the way the manipulations were done. Furthermore, we measured the user’s engagement level and emotional valence. To do so, the user wore a mobile EEG headset. All videos and neurophysiological signals were recorded and synchronized with Noldus Observer XT and Syncbox (Noldus Information Technology, Wageningen, The Netherlands) [Fig. 2].

Fig. 2.
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Three cameras installed around the task area and a GoPro camera on the chest of the participant

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3.3 Instrumentation

Dependent Variable

Installation task success was measured using many criteria (such as the completion of the task, the correctness of the wire connections, the firmness of the cable fastening). Thus, success was achieved when the participant completed the installation with few or no mistakes.

Psychometric Measures

Motivation and perceived self-efficacy were assessed with a questionnaire. User installation motivation was measured using a single item question developed specifically for this study (ranging from 1 (low motivation) to 10 (high motivation). Perceived self-efficacy was assessed with a 6-item measure [30].

Psychophysiological Measures

Psychophysiological measures were used to measure arousal, valence, and cognitive engagement [27]. We used average electrodermal activity (EDA) during the task for each participant (Fig. 3) to assess arousal. Sensors (BIOPAC, Goleta, USA) were applied in the palm of the hand of participants to measure skin conductance during the experience. Electroencephalography (EEG) (Fig. 4) was used to measure participants’ cognitive engagement [25] and valence [11] by means of a wireless EEG headset (Brainvision, Morrisville, USA).

Fig. 3.
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EDA sensors

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Fig. 4.
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EEG headset

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The EEG data was recorded from 32 Ag-AgCl preamplified electrodes mounted on the actiCap and with a brainAmp amplifier (Brainvision, Morrisville). The acquisition rate was 500 Hz and FCz was the recording reference. We used NeuroRT (Mensia, Rennes) software for the EEG processing of the data. Thus, preprocessing steps were performed in this order: down-sampling to 256 Hz, bandpass filtering with an infinite impulse response filter at 1–50 Hz, notch filtering at 60 Hz, blink removal through blind source separation, re-referencing to the common average reference, and artifact detection by computing the riemannian distance between the covariance matrix and the online mean. We used a filter bank to isolate the following bands: alpha (8–12 Hz), theta (4–8 Hz) and beta (12–30 Hz). Cognitive load was calculated with the formula beta/(alpha + theta) using the sum of channels F3, F4, O1, O2 [25]. Valence was calculated as frontal alpha asymmetry, i.e. the difference between F3 and F4 in the alpha band [11, 26]. These measures are summarized in the following Table 1.

Table 1. Psychophysiological measures
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4 Results

4.1 Attitudinal Factors

To test our hypotheses, success was used as the dependant variable in our statistical analysis. In order to test H1, suggesting a relationship between motivation and success, we used logistic regressions modelling the probability of success. Motivation was treated as binary variable (median split). Results presented in Table 2 show that motivation did not influence success. Thus, H1 was not supported. A similar test was performed for H2, which posits that users with greater self-efficacy are more successful at installing an electronic device. As no significant effect of self-efficacy was found on user success (Table 2), H2 was not supported.

Table 2. The impact of attitudinal factors on installation success
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4.2 State Factors

Concerning user state factors, logistic regressions were performed to model the marginal effect of arousal, cognitive engagement, and valence on the probability of success. Results indicate that users with higher arousal (EDA levels) were less likely to succeed (p-value = .0322). Neither cognitive engagement, nor valence had an impact on successful installation (Table 3). Thus, only H3 was supported.

Table 3. The impact of user state on installation success
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4.3 Behavior Factor

A logistic regression was performed to model the effect of reading instructions at the beginning of the task on successful installation. Results indicate that users who read instructions at the beginning were more likely to succeed (p-value = .00215, Table 4). Thus, Hypothesis H6 is supported.

Table 4. The impact of user state on installation success
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In a post hoc analysis, we decided to analyze if the level of EDA may have an impact on the reading of instructions and thus, influence the success of the experience. Actually, it is interesting to understand if a person who was highly activated during the experience would completely forget to read instructions. We explored the relation between reading the instructions and arousal (EDA) using a linear regression. Arousal was negatively related to reading instructions (p-value = .0138) (Table 5).

Table 5. The impact of user state on installation success
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5 Discussion and Concluding Comments

This research is an exploratory attempt to analyze the first stages of the user experience with a product or service; i.e. unboxing, uninstalling and installing the product even before the configuration and usage. Our results show that attitudinal, state, and behavioral factors do not necessarily all have an impact on the successful installation of a product. Our results suggest three main findings: (1) Users’ arousal negatively impacts their successful equipment installation, (2) Reading the installation instructions leads to more success, and (3) There is a relationship between reading the instructions and users’ arousal level. All other variables investigated (motivation, perceived self-efficacy, emotional valence, cognitive engagement) did not discriminate between successful and unsuccessful participants.

This study contributes to human computer-interaction literature in different ways. First, we investigated user experience prior to the actual device usage, which is a relatively understudied area of UX. Second, the study illustrates the potential of using psychophysiological measures to capture automatic and unconscious states to inform UX research. Moreover, the non-linear nature of the task also required the recording in a synchronous manner using multiple cameras, including a chest camera, to track the user behavior at any time during the experiment.

Being an exploratory research, this study has several limitations and presents avenues for further research. First, the limited sample size may have contributed to some hypotheses not being supported. Thus, future research should be performed to improve the external validity of our findings. Moreover, additional variables or even additional relationships may be investigated in the future. For instance, the relationship between arousal and self-efficacy. Bandura [2] argues that performance is impacted by a state of high arousal and may have an impact on the individual’s’ perception of self-efficacy. There could be also a relationship between cognitive engagement and self-efficacy [32]. In addition, understanding the How and Why of the relationship between arousal and reading the instructions may help the design of a better experience and increase installation success rate. Methodologically, mobile eye tracking could be used to more precisely understand actual visual attention on instructions. Moreover, even if people interacted with different electronic devices (i.e., old and new ones), we did not investigate the actual use of the new device. It would be of interest to study if users’ perception of the installation may have an impact on their first and future uses of the device.

To conclude, we tried to understand which attitudinal, psychophysiological, and behavioral factors can help a company in predicting successful electronic device installation. In the long run, this type of experience opens the door for new innovative modes of interaction and types of research in the field of User Experience and Human Computer Interaction.