Mental Workload for Bank Advisers Due to the Use of Digital Technologies

Abstract

For several years now, an increasing proportion of bank advisers’ work has been carried out using digital technologies. The COVID health crisis led to the development of videoconferencing meetings, and despite the end of the crisis, many appointments with customers are still offered by videoconferencing. A study of 349 bank advisers was carried out to examine the effect of the use of digital technologies on perceived mental workload as a function of some contextual and individual factors. Results show a change in the temporal and organizational workload and in the implementation of activity regulation strategies due to the use of digital technologies.

1. Introduction

With the integration of digital tools in the workplace, the work activity has changed. Saadi Lahlou describes this change as a kind of complete reengineering of the service sector, with far-reaching and serious changes [1]. The digitization of companies was accelerated by the arrival of the COVID-19 health crisis. This acceleration in digitalization has affected all sectors, but the banking sector has undergone real upheaval more than any other has. During the March 2020 lockdown, almost 90% of employees in the banking sector were placed in teleworking, greatly altering not only the way banks operate but also customer relations. In this context, the interaction between advisers and their customers has been mediated by digital tools more largely than before. In fact, during the period of lockdown, all banking appointments were made remotely, online, using videoconferencing, email, the messaging application, and so on. This digital transformation has continued despite the end of lockdown. It is now increasingly common for customers to demand online appointments, whether by telephone call or videoconference. This creates more work for bank advisers, receiving emails all the time, expecting an immediate or very rapid response. This digitalization therefore tends to expose employees to psychosocial risks, with a higher mental workload, compared to less digitalized sectors [2].

The aim of the study presented is to understand the relationship between the use of digital tools and mental workload and how the use of digital tools affects the mental workload of a bank adviser. The literature review is composed of a first part on mental workload and a second part on digitalizing of the customer relation. Data issued of this review will allow elaborating a hypothetical model tested by a survey. Results will be treated by generalized linear models and are discussed. Finally, we will conclude and propose some recommendations in the light of results.

2. Theoretical background

2.1 Mental workload

According to [3], mental workload can be defined as cognitive demand of a task and be estimated by psychophysiological records, performance to the task, and self-reports. Leplat [4] added that this cognitive demand varied as a function of individual resources and context of task execution. Mental workload will be thus the perception of effort necessary to perform a task. Galy [5] proposes the Individual—mental Workload—Activity Model (IWA) to describe mental workload perceived by operator. This model is centered on identification of factors responsible of the mental workload allowing to categorize it. It considers three components: individual, activity, and mental workload. Individual characteristics can be affective, cognitive, social, and physiological. Thus, as a function of affective or emotional state, available resources of individual will be too more or less high to perform a task. Work activity is defined by specific characteristics that determine a first category of mental workload and intrinsic mental load, as well as by execution context. This context integrates organizational factors (work schedules, time to shift, equip composition, etc.) that influence functional state of individuals and work conditions (work rhythm, time pressure, work-family conflict, etc.) determining extraneous mental workload. Previous studies showed that two subcategories of extraneous mental workload can be distinguished: temporal mental workload and organizational mental workload [6]. Temporal workload concerns temporal aspects of work in terms of work rhythms, cadences, task interferences, or temporal constraints. Organizational load corresponds to work organization (planning, clarity of instructions, autonomy in work, etc.) and social ambience (relation with hierarchy and colleagues, job recognition, etc.). A last category of mental workload is characterized, which is the germane load. It corresponds to mental cost of adaptation strategies. Implementation of these strategies of work activity regulation allows individuals to adapt to the constraints imposed by task or context and maintain performance. Germane load depends thus on task characteristics (an easy task will mobilize little germane load because meta-cognitive processes or particular strategies will not be necessary) and individuals’ characteristics (expertise to task will permit to implement easier adapted strategies; on the contrary, stereotype threat, for example, will prevent implementation of adapted strategies). Relationships between these categories of mental workload and factors of load are represented in Figure 1.

Figure 1.

Representation of IWA model.

As a function of task characteristics and work context, intrinsic and extraneous loads will be more or less high and draw on the available resources of individuals. Remaining resources can be allocated to germane load. Temporal workload and organizational workload have opposite effects on germane load. A study conducted by Galy [6] on 616 participants showed that germane load is high when temporal aspects of external load are high and when external load due to organization and social ambiance in work is low (Figure 2). Organizational workload creates constraints that do not allow individuals to regulate their activity, while regulatory strategies can be implemented to compensate for time constraints.

Figure 2.

Schematic representation of relationships between mental workload categories revealed by generalized additive models analyses. Full lines represent positive relationships. Dotted lines represent negative relationships.

The IWA Model of mental workload has given rise to a rating scale of mental workload used in the present study [6].

2.2 Digitalizing the customer relation

Digitizing the customer relationship seems to be a matter of strategic priority because creating a lasting customer relationship is at the heart of the strategy [7]. Customers are connected to all types of digital media, computers, tablets, smartphones, and so forth, and can interact 24/7. The customer therefore requires an instantaneous customer relationship. The health crisis has played a role in accelerating the digitalization of the banking sector by promoting digital contacts, whether by telephone, videoconference, or via their applications, to communicate with their customers. The aim is to consider customers in their own environment, that is, from their smartphone, computer, and so on. To achieve this, companies are making new resources available to customers to maintain and develop their customer relationships.

In the case of banks, we can talk about “multi-channeling,” which is the integration of all communication channels in order to offer customers a harmonious experience [8]. Multi-channeling suggests the possibility for customers to contact their adviser by different channels: telephone calls, messages, emails, video-conferencing, and so forth. Multi-channeling creates a fusion of channels and therefore meets the customer’s need for fluidity [9], giving them the feeling of being present in all places simultaneously [10].

The concept of meta-work is increasingly present because of digital tools. Meta-work is defined as “any work that makes work possible” [11]. It represents work added on top of the main work. This leads to an increase in activities such as organizing tasks and coordinating activities. Meta-work therefore corresponds to factors of extraneous workload and particularly organizational workload. New activities are also emerging, such as immediate exchanges and the management of permanent information flows, and employees can easily find themselves with an information overload to be processed very quickly, increasing work cadences. They have several digital tools at their disposal (computers, tablets, and mobile phones) that enable them to carry out many tasks simultaneously, but their activity is fragmented by the constant influx of new information. These elements participate in an increase of temporal mental workload.

A previous study conducted on teleconsultants highlighted the constraints, as well as the advantages, associated with the use of digital tools [12]. These tools made employees more efficient but required a learning and adaptation phase, which can be likened to an additional task. This new task consumes resources and requires voluntary effort, which can contribute to exhaustion and lead to poor working conditions [13]. Employees need to be supported and given time to assimilate [14]. Thus, in the present study, we consider digital fluency like a factor of mental workload.

These effects of digitalization are likely to be more pronounced in women than in men. Because even today, in the context of long-term planning and decision-making, women devote more mental energy to anticipating the demands of parenthood and reconciling partners’ competing career needs [15, 16].

3. Hypotheses

The hypothetical model tested the interaction between individual characteristics and task characteristics to explain perceived mental workload. The details of this model are shown in Figure 3.

Figure 3.

Hypothetical model.

Individual characteristics were gender, digital fluency, age, and length of service. Task characteristics were task difficulty, number of videoconference appointments, and number of face-to-face appointments.

Considering the presented background, we assume that gender will determine available resources with lower resources for women than for men. Task difficulty will determine intrinsic mental workload. Intrinsic load will be higher when task difficulty will be perceived high. Number of videoconference and face-to-face appointments will determine the organizational and temporal mental workloads. Particularly, we assume that temporal workload increases with an increase of number of videoconference and face-to-face appointments and that a high number of videoconference appointments will be related to a high organizational workload. Finally, available resources, digital fluency, age, length service, and other categories of mental workload will determine germane mental workload. Thus, according to IWA model, germane load will be high when intrinsic and temporal loads will also be high and when available resources and organization load will be low. Digital fluency, age, and length of service will have a positive effect on germane workload because these factors are the reflection of an expertise that favors the implementation of regulatory strategies responsible for a high germane load.

4. Methods

4.1 Participants

About 349 participants composed the final sample, all bank advisers aged between 21 and 56, with an average age of 33.7 and a median of 33. Of these, 276 were women and 73 were men. They had 10.2 years (±7.09) of length of service.

4.2 Materiel

A questionnaire was elaborated. The first part was the consent to participate in the study. The second part interrogated on the use of digital tools. It comprised questions on the frequency of face-to-face and videoconference appointments expressed as a number of appointments by day and on digital fluency (How comfortable do you think you are with the digital tools you use in your day-to-day work? By asking on an eight-degree scale from not very comfortable to very comfortable). A third part was the IWA questionnaire [5] composed of five dimensions: available resources (9 items), intrinsic mental workload (4 items), organizational mental workload (10 items), temporal mental workload (7 items), and germane mental workload (10 items). For each item, participants answered on a scale of eight degrees from strongly disagree to strongly agree. Finally, participants were asked some sociodemographic questions (gender, age, and length of service).

4.3 Procedure

The questionnaire was distributed mainly on a group dedicated to bank advisers on Facebook and was also sent to bank advisers via LinkedIn. The questionnaire remained available for 1 week. Participants were informed of their right to data processing anonymity and their right of withdrawal at the start of the survey. All questions were required, and participants could not move on to the next questions if they had forgotten to answer a question. Once they had answered the questions, participants could not go back. At the end, a thank-you message appeared, indicating that the participant’s answers had been recorded.

5. Results

Recollected data have been treated by generalized linear models with the software Jamovi.

5.1 Descriptive analyses of mental workload dimensions

Table 1 presents mean and standard error for available resources, intrinsic load, organization load, temporal load, and germane load. With single-sample T-test, we compare the obtained means and reference values described by Galy [6] in order to determine the criticality of work situation. The reference value is 4 for available resources, organization load, and temporal load and 6 for germane load. No reference value is reported for intrinsic load.

Dimensions	Mean	Standard Error	T-test
Available resources	3.38	1.40	−8.18**
Intrinsic load	5.66	1.10
Organization load	4.25	1.25	3.78**
Temporal load	6.88	.988	54.54**
Germane load	6.37	.873	7.85*

Table 1.

Descriptive analyses.

*

indicates p<.01; ** indicates p < .001.

For each dimension, minimal score was 1 and maximal score was 8. Results show that available resources are low and significantly lower than reference value. Organizational and temporal loads are high and significantly higher than reference value. Finally, germane load seems near to reference value (6), but it exists a significant difference between mean of germane load and reference value indicating a germane load higher than this one.

5.2 Determinants of available resources

The model explicating the most part of variance and with the best statistical powerful was composed of digital fluency, gender, and task difficulty perception (r² = .318; AIC = 997.772). Available resources were higher when participants were more comfortable with the use of digital tools (β = .144; p < .01), for men than for women (β = −.791; p < .001), and when task was perceived easier (β = −.328; p < .001).

5.3 Determinants of intrinsic mental workload

Concerning the factors explaining intrinsic workload variation, only task difficulty perception is significant (r² = .0627; AIC = 923.9360). Intrinsic mental workload increased when the task difficulty was perceived higher (β = .131; p < .001).

5.4 Determinants of organizational mental workload

The better model indicates two factors determining the organizational mental workload, digital fluency, and task difficulty perception (r² = .0985; AIC = 994.9030). These factors were acting in opposite directions with an increase of organizational workload when the digital fluency was low (β = −.178; p < .001) or when task was perceived difficult (β = .158; p < .001).

5.5 Determinants of temporal mental workload

Generalized linear model shows a significant effect of age, gender, task difficulty perception, and number of videoconference appointments on temporal workload (r² = .197; AIC = 832.123). Temporal workload is estimated higher by women than by men (β = .278; p < .05), when participants are older (β = .029; p < .05), when tasks are perceived difficult (β = .165; p < .001), and when the videoconference appointment number is low (β = −.049; p < .001).

5.6 Determinants of germane mental workload

Finally, the last analysis reveals that gender, length of service, digital fluency, task difficulty perception, available resources, and organizational workload are a significant effect of germane mental workload (r² = .161; AIC = 849.128). Results show that germane load is higher in women than in men (β = .249; p < .05), when participants are more comfortable with digital tools (β = .194; p < .001), when the task is perceived difficult (β = .055; p < .05), when available resources are high (β = .107; p < .01), and when organizational load is low (β = −.116; p < .01).

5.7 Mediation analyses

Previous generalized linear models highlight the probable mediation of available resources of the effect of task difficulty on germane load, mediation of organizational load of this same effect, and mediation of organizational load of effect of digital fluency on germane load. Analyses of mediation reveal a partial mediation of available resources on the effect of task difficulty on germane mental workload (indirect effect: z = −4.078, p < .001, % mediation = 46.7) and a partial mediation of organizational load on effect of task difficulty on germane load (indirect effect: z = −3.514, p < .001, % mediation = 44.1). Thus, the effect of task difficulty on germane load is mediated by available resources and organizational load. When the task difficulty is high, available resources are low and organizational load is high, resulting in a decrease of germane load.

5.8 Observed model

With all the obtained results, we can represent the model presented in Figure 4.

Figure 4.

Observed model. Full lines represent positive relationship and dotted lines represent negative relationship.

Globally, our results reveal direct effects of individual characteristics on germane mental workload and indirect effects of task characteristics. Three individual characteristics (gender, digital fluency, and length of service) determine germane load. Participants are able to regulate activity when they are males, comfortable with technology, and long-standing. The phenomenon is reinforced by the presence of high resources, themselves determined by gender, digital fluency, and task difficulty. Resources decrease when task difficulty increases. Task difficulty determines intrinsic mental workload as well as organizational and temporal loads. When task difficulty increases, these three categories of mental workload increase too. Concerning the appointments, only the number of videoconference appointments seems to play a part in the model with a negative relationship with temporal load indicating that a high number of videoconference appointments decreases the temporal load.

6. Discussion

The obtained model, while different from the hypothetical model, is quite close to it. It confirms that mental workload can be categorized in several dimensions because these dimensions are determined by different factors and that different categories of mental workload have asymmetric relationships. Indeed, germane load is determined by others categories of mental load (organizational and temporal loads) and available resources. These results are in agreement with previous studies [5, 6].

Data show that surveyed bank advisers experience problematic work situations in term of mental workload. Indeed, they express high organizational and temporal mental loads associated with low resources. However, this seems to be compensated by activity regulation, since the germane load is higher than the threshold value of 6. This ability to regulate activity varies according to the resources available to individuals and the organizational and temporal constraints they face. When constraints are severe, the individuals with the most difficulty are those with the fewest resources.

Two factors related to technology use seem to reduce constraints. Contrary to our expectations, the deployment of videoconferencing leads to a reduction in temporal workload, while the face-to-face appointment number has no effect on mental workload. Thus, videoconferencing appointments would reduce the need to implement regulation strategies by decreasing temporal mental load. Consequently, for our population, contrary to what Bonneau and Enel [11] report, the use of these digital tools does not appear to be at the origin of additional meta-work tasks. There are, however, inter-individual differences.

Digital fluency has a negative relationship with organizational load and a positive relationship with germane load. This result is in line with those obtained by Le Gonidec and collaborators [12], which show that when tools are mastered, they help maintain work performance. Indeed, different levels of digital fluency can be considered like different levels of expertise in technology use. Experts are able to have high efficiency in some tasks because they develop specific strategies to the task, allowing to decrease the cognitive cost of information processing. Thus, the experts are able to establish an efficacy planning and to adopt behaviors making them efficient in the task execution [17]. They elaborate schemes allowing to categorize and to aggregate elements. The more an individual is expert in a field, the more he has schemes in memory and the less the task will be cost cognitively. The experience permits experts to elaborate new schemes more quickly, and the knowledge permits them to apply the best strategies as a function of the task [18]. Thus, the implementation of strategies by experts favoring performance to the task would correspond effectively to the solicitation of germane load of IWA model. This result highlights the importance of formation to reduce mental workload of workers. In our case, the mastery of digital tools is at the root of a reduction in organizational workload and favors the implementation of more efficient regulation strategies. This interpretation is reinforced by the effect of length of service on temporal and germane loads too. High length of service is associated to a more important expertise, and the longest-serving bank advisers have the lowest temporal mental workload and the highest germane mental workload.

According to our hypotheses, gender determines available resources, as well as temporal load and germane load. They report higher temporal and germane loads despite lower resources. Work situation seems be more critical for women than for men. These differences can be explained by the fact that mental workload is added to that generated by family activities [15, 16].

7. Conclusion

Our study highlights that the use of new technologies actually represents a cognitive cost for bank advisers since poor skills in the use of new technologies increase the organizational workload and reduce available resources. However, when the tools are mastered, they can reduce the external mental load and promote the implementation of regulation strategies improving professional satisfaction and subjective performance at work [6]. Thus, these results show that the introduction of digital technologies needs to be considered in the context of overall work organization. Bank advisers’ training prior to deployment seems to be essential to ensure that a work situation is not created that generates a deleterious workload with repercussions on individual work performance.