The Consideration of Job Satisfaction in the Design of Assistance Systems in Production

The design of the work has been a focus of work psychological research for decades. In particular, with the steady development of new automated systems, this area is becoming increasingly important. The literature shows that a variety of factors influence constructs such as job satisfaction or the overall well-being of employees. One of the basic theories for the beneficial design of work is the Job Characteristics Model (see [7]), which focuses on the core job dimensions of skill variety, task identity, task significance, autonomy and feedback. Over time, the central factors have been expanded and knowledge-based characteristics and physical aspects were also included (for an overview see [12] and [15]).

Another theory is the two-factor theory according to Herzberg et al. [11], which distinguishes between motivators and hygiene factors. Hacker [8] describes further key aspects for the design of beneficial work, whereby the completeness of the work is emphasized here. An activity is complete when the employee is involved in all phases (organizing, planning, executing and controlling), which Hacker also calls “sequentially complete” work. Another aspect, the “hierarchical completeness”, describes task profiles, which include both complex and less complex activities. According to Hacker, central aspects to be considered when assessing a job are monotony, problem-solving ability, the ability to learn to work and the importance of control and autonomy. If the completeness of work is not given, the learning and development opportunities of the worker are limited, which in turn has a negative effect on motivation, well-being and personal development of the worker.

Karasek [13] describes the Job Demand & Control model, which deals with the relationship between job demands and job decision latitude in relation to the general experience of stress and strain in the work context. According to the model, job demands and job decision latitude can vary independently and, depending on the relation to each other, lead to the employee’s stress or positive experience of the activity.

From the literature above, the central aspects of designing conducive work have been summarized for the MMAssist project (https://​www.​mmassist.​at/​). Based on the approach of the evaluation framework in the FACTS4WORKERS project (https://​facts4workers.​eu/​, see [9]), which referred to the dimensions of autonomy, competence, variety, relatedness, protection, efficiency and quality, we presented the dimensions in a more differentiated manner, based on the work of Morgenson and Humphrey (see [12] and [15]). As a result, we have used for our framework the dimensions of task level (variety of tasks, autonomy in terms of decisions, temporal and content organization of the task, etc.), knowledge level (complexity of the task, problem-solving skills, variety of skills, information processing, etc.), social level (social support, interaction with colleagues) and work context (physical requirements, working environment) for the description of the work-related factors.

Previous work design studies describe a variety of factors to consider when (re)designing work, as is the case with the introduction of new technologies. The difference between assistance systems and high-automation systems is that the first support people at work, while the second need people as supporters. As this publication concentrates on assistance systems rather than high-automation systems, the human factor problems are not to be seen in the area of monitoring and transition problems, but rather in designing the assistance systems so that they can offer usable support. The approach to the development of assistance systems is therefore even more directly bounded to the human user and requires the understanding of what exactly should be supported.

Effects of automated systems on various outcome variables, such as employee job satisfaction, have been studied for decades (see [10]). Basic theoretical formulations were postulated by Wall et al. [17], who saw four major areas influenced by the introduction of automated systems: employee autonomy (temporal, methodical and task control), cognitive requirements (monitoring and problem-solving skills), Change of responsibilities and social interactions. The direction of the effects (positive or negative) depends mainly on the design of the automated system and the way it is connected.

Similarly, Cascio and Montealegre [4] describe the relationship between automated systems and employee demands. Reduced control and autonomy of the employee while at the same time perceived increased work demands threaten to bring negative effects to the introduction of automated systems. Likewise, Baethge-Kinsky and Tullius [2] highlight the change in the requirement structure, which relates in particular to analytical and problem-solving competence, but also requires additional knowledge of operational processes, social-communicative and self-organizational skills.

Based on the historical development of assistance systems, Mital and Pennathur [14] argue that technological developments tend to de-qualify workers rather than helping people achieve more self-determination and more fulfilling work. They therefore see the further development of the abilities of the employees as a central point, which must be considered when introducing new systems.

Experimental studies, such as Bala and Venkatesh [3], report negative effects of assistance systems on the experience of employees in terms of requirement and freedom of action - especially in the initial implementation phase of assistance systems - which in turn reflected reduced levels of employee job satisfaction. However, these effects were dependent on the system characteristics of the assistance system.

Especially with the introduction of assistance systems, it requires the conversion and the support of the workers in order to prepare and adapt the system accordingly. Such often quite flexible and adaptive activities are difficult to prescribe and more likely to emerge through experimentation and active recognition of customization options. These interactions require a positive, interested, and open attitude towards the system, so a high system acceptance. This makes it possible not to perceive change and restructuring as a threat, but to face it with confidence and participation.

Above all, the connection between the changing role of workers resulting from assistance and job satisfaction is essential. For example, a shift in roles may result from a shift in activity towards increased supervision activities of workers, which could be positively or negatively evaluated by them, thereby having an impact on overall job satisfaction. Another case could be that while workers prepare the assistance for other workers, they do not receive benefits themselves. The addition of such new activities without own benefits could have a slightly negative impact on workers acceptance and job satisfaction and should be considered (Fig. 2).