4.1.2.2. A triple mediation

4.2.1. The individual in the design phase

4.2.1.1. From creator to innovator

Innovation is not reduced to a creation, an invention. It is the result of a design activity that has been adopted by a market. At the end of the day, the aim is to bring profitable products to market. As a result, product design is much more use-oriented.

With regard to product innovation, for most of the 20th Century, it was the technology push model (technological progress conquering the market) that dominated (see Chapter 2). This was particularly the case in the telecommunications, aerospace, nuclear and robotics industries, under the influence of public policies and associated funding. In this model, innovation is the result of scientific and technological progress. Based on technological determinism, innovation is designed and then delivered to society or markets in a linear and mechanical manner with a top-down vision.

At the end of the 20th Century, this vision was followed by that of market pull (products marketed were inspired by the consumer), based on taking the customer into account as a key player in defining needs. This started from market expectations and aimed to adapt or promote technologies. Marketing was at the heart of the system. In companies, R&D designers were in the position to act as internal service providers at the service of marketing to provide technical solutions to needs expressed in functional terms. Although there may still be technological innovations born from the technology push model (Apple’s iPad is a good example), most innovations are nowadays born from a market pull vision.

The 1990s saw the arrival of a radically new concept. The expertise present in a company gave it a sustainable competitive advantage in its market in the name of its ability to generate innovation in its products or services. Companies witnessed the rapid wear and tear and obsolescence of the knowledge of its businesses and technologies. The rapid commercialization of products required the acceleration of innovation processes and cost pressure to streamline design activities.

The designer’s romantic vision, seen as a hero rewarded for their autonomous and independent work, is flawed, even in areas that seemed a priori the most creative. In the video game sector, for example, rationalization and customer orientation impose their law and work is segmented into a multitude of skilled trades. This sector of activity is maturing and includes large companies whose operations are far from the start-up model that dominated at the beginning. We are now speaking of organizations such as those found in the industrial world (see Box 4.2).

4.2.1.2. A design shared between humans and machines?

While the technical innovations in the digital field result from a design activity, this activity is, in turn, increasingly structured by digital technology such that it is not an exaggeration to talk today about a sharing of design between humans and machines.

In industry, the future of engineering and R&D professions is strongly linked to the development of PLM (Product Lifecycle Management) digital platforms that introduce new ways of working. These tools facilitate the organizational and geographical fragmentation of value chains and, while they can provide valuable assistance in terms of knowledge capitalization, they also tend towards a certain automatism. They result in a greater formalization of activities, with new tool intelligence obligations, for example, and questions are raised as to whether they are a form of support or an obstacle to creativity and innovation (Paraponaris et al., 2018). However, when faced with complex work situations, design engineers take different perspectives and do not converge on describing a single situation. While some mentioned the difficulty of achieving cohesion in their work incurred by the use of these design tools, others noted a harmony facilitated by these same tools and a more fluid collaboration.

Digital R&D is now seen as having very high stakes, which places it at the forefront of the concerns of company management (scientific and information systems departments), and as one of the prominent sources of questioning (if not concern) for R&D professionals. It is certain that digital technology will change R&D work and the professionalism of researchers and engineers, with uncertainty about the nature and depth of these transformations. For R&D managers, this calls for vigilance and consideration of ways to support these changes in work by promoting the necessary learning dynamics. For researchers, this invites them to take the initial work on these issues further.

4.2.2. The individual in the adoption phase³

4.2.2.1. The diffusionist point of view

Supporters of the diffusionist movement do not pay attention to the technical object’s design phase, of what is related to its genesis. They focus, on the one hand, on how innovations are disseminated and who their users are (the adopters) by developing behavioral models, and, on the other hand, on measuring the impact of their adoption through changes in practices.

This point of view is particularly embodied by Everett Rogers (1983), author of the diffusion of innovations theory developed from the summary of the results of various studies. According to Rogers, it is the characteristics of innovation, as perceived by individuals, that determine its adoption rate. He identifies five characteristic attributes of an innovation: its relative advantage, its compatibility with the pre-existing system, its complexity, its trialability and its observed effects.

This typology has been well received by marketing. The research resulting from it generally has a prescriptive purpose, seeking to explain disparities in an innovation’s adoption level by correlating them, through questionnaire surveys, with traditional socio-demographic variables: age, sex, occupation, income, housing, family size, etc. The groups that result from it are interpreted as customer segments. In addition, product marketing can involve opinion leaders who are the most supportive of innovation.

This theory classifies individuals, users of innovation, according to five standard profiles: innovators, early adopters, early majority, late majority and laggards. We provide a brief definition, inspired by Rogers (1983) and expressed from a marketing perspective:

• – innovators are the most sensitive to innovation. They are the first consumers of a new product as soon as it is released. They make their purchases without having to consult the opinions of other users. They are more motivated than others by the status conferred by a new product. These customers like to share their experience with others on something new;
• – the early adopters quickly buy an innovative product. They are people who like new things, they try them out and give their opinion. They show more active social participation and have a denser and more diversified interpersonal network than the late majority. They also show a higher degree of opinion leadership. They contribute using these characteristics to the triggering of the critical mass formed by the early majority;
• – those of the early majority are thoughtful customers. They await feedback from the first experiences before buying a new product;
• – the late majority expects the product to be used by a significant part of the population. The individuals who constitute it want proof of performance. They are very influenced by the opinions of other users and want to know to what extent a new object is better than others that are already on the market;
• – the laggards are the last to accept an innovation. They are the most rational customers. They only buy new products when they have been tested and become commonplace or even when they are part of a tradition.

The originality of this approach is that it integrates the classification of adopters into different categories by considering the reception of an innovation on a time scale: the profile of adopters moves from a small and marginal group to a larger group, and then to a pool covering the entire population.

This view, which praises innovators, suffers from a bias in favor of innovation. As such, it has been the subject of much criticism, particularly from the sociology of innovation (Akrich et al., 2006). Moreover, by equating diffusion with an inevitable and irreversible phenomenon, it does not take into account the possible rejection of innovation by the adopter at any time (“abandoners”), and not only during the initial decision-making process.

Finally, in line with our reflections on determinism (see Chapter 1), it is clear that diffusionism expresses a certain economic determinism. Indeed, we can highlight a static vision of innovation, an idea that is part of an instrumental conception of innovation: transformed into a marketable product, responding to a need that it is able to satisfy, it would no longer be transformed.

4.2.2.2. The acceptance model

Unlike diffusionism, which, by focusing on studying the process of technology diffusion through the evolution of an adoption rate, embraces the innovation promoter’s point of view, the study of uses in terms of acceptance and acceptability adopts the point of view of users.

The approaches that claim to use this perspective are numerous and sometimes contradictory, but they converge on the idea of technological non-determinism: to be accepted, a technology must be re-appropriated by the user.

Among the most well-known theoretical models, Davis’ (1989) Technology Acceptance Model (TAM) is the reference point (see Figure 4.1). For the TAM, the effects of beliefs on utility and perceived ease of use are the main determinants of user acceptance of the technology. These normative beliefs are assessed by the respondent’s feeling expressed in a questionnaire about his or her approval (or disapproval) of items related to these two factors.

Perceived usefulness is “the degree to which a person believes that using a particular system would enhance his or her job performance” (Davis, 1989). The perceived usefulness will be high if the individual thinks that:

• – the system will allow him/her to learn faster;
• – using the system will not be a waste of time;
• – the system will make it easier to learn;
• – the system will be very useful for learning.

Research has shown that perceived usefulness can be affected by multiple variables, which fall into three categories. A first category covers the characteristics of the user (age, sex, professional category, seniority, etc.). A second relates to organizational functioning (support from external leaders or consultants, communication policy, social influences of professional groups, etc.). A third concerns the characteristics of the technological team itself (functionalities offered, ergonomic quality, task/technology suitability, etc.).

Perceived ease-of-use refers to “the degree to which a person believes that using a particular system would be free from effort” (David, 1989, p. 320). Perceived ease-of-use is related to items such as:

• – using the system will be easy for him/her;
• – the system will be flexible to use;
• – no problems will be encountered when using the system;
• – it will be easy to find out how to use the system.

Originally, the TAM was used to explain the adoption of applications such as word processing, internal e-mail and video conferencing. Its application now extends to practices concerning the general public (social media, mobile Internet).

4.2.3. The individual in the use phase

The acceptance of the technology and its use do not necessarily overlap. While acceptance, particularly in Davis’ case, is a matter of attitude, use is a matter of behavior.

4.2.3.1. The located acceptance

In the context of real use, the question is no longer that of the acceptability of the technological object, but what it allows (or does not allow) one to do or obliges (or does not oblige) one to do. With this in mind, Bobillier Chaumon’s (2016) work focuses on testing technology in real-life situations, what he calls “situated acceptance”, i.e. the concrete experience of the tool in real life. For this occupational psychologist, the individual and personal dimension – that relating to the operator’s own activities, in their cognitive and emotional aspects – is not the only one to be taken into consideration. There are also three other dimensions to consider:

• – the organizational dimension, which involves the operator’s relationship with the organization of work, in particular the control exercised by the technological equipment over its actions;
• – the interpersonal dimension, relating to the collective activities in which the operator is involved and which may be affected by the technological equipment;
• – the identity and professional dimension, which concerns the individual’s “power to act” and their ability to have their professional identity recognized.

4.2.3.2. Towards a unified model of acceptance and use?

In response to the profusion of models, Venkatesh et al. (2003) proposed a unified model of technology acceptance and use, called UTAUT (Unified

Theory of Acceptance and Use of Technology). This model, which incorporates the most significant elements of the eight theories considered most important at the time, justifies the use of ICTs based on four fundamental determinants of behavioral intent defined as follows:

• – performance expectancy: the degree to which a person believes that the use of technological equipment will help them to achieve gains in their work performance;
• – effort expectancy: the degree of ease associated with the use of the technological equipment;
• – social influence: the effect of environmental factors such as the opinions of a user’s friends, relatives and superiors on user behavior;
• – facilitating conditions: the extent to which a person believes that an organizational and technical infrastructure exists to support the use of technological equipment.

Such models are well suited for research, but seem unwieldy in real life. However, their contribution to managerial thinking cannot be ignored (see the example in Box 4.3).

4.2.3.3. The symbiotic approach

The symbiotic approach does not separate adoption from use, considering it as an ongoing process. Based on Licklider’s (1960) theory that sees the computer as a symbiont (an organism that lives in symbiosis with humans), it involves a very close coupling between humans and technical objects. The anthropomorphic semantics of the symbiotic approach focuses on the emergence of devices that mimic the cognitive capacities of human beings in which human and non-human registers are merged. This approach, which has been closely linked from the outset with the scientific and industrial community of artificial intelligence, is enjoying a resurgence in popularity.

For Brangier, Dufresne and Hammes-Adélé (2009), who are part of this trend, the dominant paradigm, of technology as an entity external to humans who are conceived as acceptance agents deciding whether or not to use a technology, is outdated. Indeed, it is not in harmony with a world in which technological artifacts are taking up more and more space in the activities of humans, who are transferring some of their skills to them, with technological equipment becoming a part of themselves. Since humans and technologies are mutually dependent and interact, these authors evoke a techno-symbiosis, noting that individuals can no longer carry out certain activities today without their techno-symbionts, which have become human extensions.

The case reported in Box 4.4 seems to us to illustrate this symbiosis. In this case, the “social network” is not an agreed expression, but a reality where the social and digital are combined and where we find the spirit of community and freedom that marked the origins of the Internet. It also shows that digital technology can be a means of social inclusion.

4.3.1. Variable effects depending on the technological equipment

Not all technologies are equal in the way they constrain or, on the contrary, empower users. In his study of the organizational properties of digital technologies in the workplace, Bobillier Chaumon (2013) distinguishes three types of technologies, depending on the room for maneuver they leave to the individual.

The first category includes prescriptive technologies, including technological equipment that places high constraints on the activity: ERP, workflows, certain business software packages with frozen scripts, such as in call centers. Requiring the application of strict procedures for the execution of simple and repetitive (and therefore formalizable) tasks, these ICTs closely restrict the individual’s ability to take initiative. Technology makes individuals dependent, telling them what to do and how to do it. This is the world of neo-Taylorism.

The second category is composed of flexible technologies that offer resources and means to the individual to imagine and realize the full scope of their projects. We will have here, for example, office software, messaging, the Internet, smartphones and design tools for architects and engineers. However, Bobillier Chaumon notes that these ICTs can also lead to a form of prescription of subjectivity when individuals’ behavior is required to be similar to the machines they use, including injunctions to be more innovative and more efficient, etc.

The discretionary technologies in the third category are at the confluence of the two previous ones, in that they provide a possible framework for action which the individual can use at will. They guide and inspire the user in their task, who can, at any time, abandon and go beyond it to develop their own work. This category includes digital corporate networks and knowledge management tools. Here, the constraint is more subtle than in prescriptive technologies since it depends on an individual’s “free” commitment to collective norms, often from peer groups.

These distinctions overlap with those between prescriptive technologies and decision- or implementation-support technologies discussed in the previous chapter.

4.3.2. The emergence of new work characteristics

As Brangier and Valléry (2004, pp. 216–217) point out, new characteristics of work appear with digital technology:

• – the relationship between the pace of work and the pace of productivity is evolving towards an asynchronous mode. It is redefined to take into account the fluidity of the process;
• – working time no longer determines productivity, which now depends more on the profitability of the installations and the machine time consumed than on direct intervention by agents. The operator becomes “a controller of the fluidity and capacity of the process” (see Box 4.6).

The traditional conception of the company can therefore also be challenged, with new forms of production and distribution emerging. We are thinking, in particular, of online platforms and the transformation of the activities they have brought about for taxis, real estate agencies, hotels and craftsmen. To take only the example of drivers, who are now isolated, they buy and maintain their own vehicles, bearing the risk of variations in frequency alone, investments and commercial risks not being covered by the site or the exchange platform.

Digital technology is changing the conditions in which work is carried out, in particular, it is facilitating the growth of teleworking and shared workspaces, since Wi-Fi and the cloud (storing data on remote servers) now make it possible to work almost anywhere.

4.3.3. The growth of telework

Telework could rightly be considered as emblematic of the transformations that have affected the world of work since the mid-1990s (Vayre, 2019). On the one hand, it is part of the gradual erasure of the work/non-work boundary. On the other hand, it meets the requirements of new forms of work that call for autonomy, empowerment and subjective engagement of employees. While it may have initially appeared mainly as a concession to workers – a social benefit – the influence of economic and societal factors in its development should not be overlooked.

The conception of work has evolved, both among managers and employees. Companies are developing new forms of working time arrangements in response to the requirements of productive efficiency (better work organization, fight against time-consuming activities, etc.). Changes in work organization also respond to a need of employees who have greater flexibility in carrying out their work and, for the most qualified categories, wish to extend it to monitoring the balance between their professional and private lives. In this sense, telework is a response to the movement to erase the boundaries between work and non-work that we mentioned at the beginning of this chapter and which has been greatly facilitated by the use of digital technologies.

After optimizing the productivity of their industrial activities, companies have made efforts to increase the competitiveness of their tertiary activities. It is on these that international competitiveness will focus in the future, as it has focused in previous decades on increasing industrial productivity. The service has become a sector of activity in which companies generate a substantial part of their turnover. In addition to this tertiarization of the economy, there is also the need to get closer to the consumer – or end-user – of the product. Telework appears to be a competitive organization of the tertiary sector providing elements to meet these new efficiency constraints within the new flexible economy.

Finally, telework is also a mass social phenomenon, affecting 10–20% of the working population in industrialized countries. It is a response to automobile congestion in metropolitan areas, the increase in transport times and the costs involved.

As for the effects of telework in the professional, family and social fields, the literature review conducted by Vayre (2019) shows contrasting results. In the professional field, on the one hand, telework contributes to concentration, productivity, efficiency and quality of work, performance, as well as to a sense of control over work (time, task, organization), autonomy and motivation at work, organizational involvement and job satisfaction. On the other hand, it also has negative effects such as loneliness, isolation, professional exclusion, misunderstanding and hostility of the professional environment, reduction in the volume and quality of exchanges with the professional environment, or even a brake on career development and promotions. However, she notes, telework covers multifaceted situations whose impacts are balanced by moderating factors that nuance the effects of telework. These factors can be positive, such as the physical layout of the home, the technical and material support of the company, the support of the hierarchy and colleagues, or negative, such as the place of telework (exclusively home vs. dedicated professional spaces), and the intensity of telework (at home full-time or part-time).

4.4.1.1. Definition and the stakes of skills

While the term skills is widely used, it does not mean that it has a unique meaning. When an orientation psychologist, a specialist in “skills assessment”, meets an ergonomist, a specialist in “skills analysis”, or even a head-hunter, a specialist in “skills assessment”, and both use the term “skills”, it is not clear whether they mean the same thing. Our reference to activity leads us here to favor the ergonomics of human activity, which has also developed as robotization and computerization have spread, thus transferring repetitive manual tasks to automata. De Montmollin (1995, p. 78) is one of the few authors who has focused on clarifying the meaning of the concept of ergonomic skills: “Skills correspond to the hypothetical structures […] that allow the operator to give meaning, for action, to work situations (and in particular the information they provide). The skills are therefore described from the point of view of the activity. We always talk about skills for a particular task, or a particular type of task” (authors’ translation).

Within companies, new technologies have made tasks more complex, developed mental work and justified going beyond the level of task analysis alone to approach work analysis in terms of cognitive processes. At the same time, verbal activity has become more important. Today, in increasingly automated companies, work is becoming dematerialized. Until recently, the model for recognizing operators’ qualifications was largely based on industrial work based on physical effort and gestural skills practiced on the material. Then, with the implementation of new technologies, it was technoscientific knowledge that was given priority. Today, professional skills are no longer reduced to their technical aspects. Changes in work, due to the search for new forms of flexibility, are based on interpersonal cooperation and a broad understanding of the work process. They therefore require new skills from operators, skills that are more a matter of professional conduct, “interdisciplinary skills”, than the technicality of a profession; also, some people mention, for want of anything better, the need to develop soft skills.

4.4.1.2. Acquisition and development of digital skills

We are now leaving the field of ergonomics, the development of skills being usually the field of trainers. However, it would be simplistic, as we will see, to limit the production of skills to training activities only.

Interest in skills development is usually linked – by consulting firms, large companies and national and international organizations – to a staff approach to human capital. This refers to the body of knowledge and skills that a population possesses. Investment in this capital is expected to determine the company’s profitability and competitiveness. We are therefore interested in the modalities of acquiring this capital, assuming that the expenses incurred are investments. Human capital is supposed to reflect the value attributed to the qualities in which we invest. The state of this capital is assessed by considering the level and duration of training or by carrying out skills analyses.

To judge its dynamics (the way it is constituted), it is undoubtedly necessary to examine the pedagogical mechanisms, as well as the concrete work situations and their modalities of regulation. Indeed, while school and professional training can play an important role, they are not the only vectors. Many of the basic digital skills are acquired in the field, through practice, observation, participation, exchange and support. Of course, it is quite different when it comes to training in advanced technologies in order to change jobs, such as becoming a developer, digital content producer or digital project manager. But, just as it is now possible to drive a car without being a motorist, it is very easy to skillfully surf the Internet to compile documentation on a specific subject, without knowing the protocols used for data transfer that allow this research.

4.4.1.3. Digital training and training using digital technology

Digital training is offered with a variety of content. At the European Union (EU) level, eight key skills (combinations of knowledge, competencies and attitudes) have been defined which are considered necessary for personal development, active citizenship, social inclusion and employment (European Commission, 2012). Digital skills are one of them, promoted in the same way and separately as basic science and technology skills. In fact, almost all EU countries have put in place national strategies for the development of e-skills.

Symmetrically, the use of ICT as a teaching tool is also seen as promoting the development of interdisciplinary skills and, as such, highlighted in national education policies. The situation varies from country to country.

Thus, for example, from the selection in Table 4.2, all countries agree that the use of ICT in education programs promotes analytical skills development and collaboration, while the acquisition of other skills is not considered by all to be related to the use of digital technology.

The EU notes that the presence of equipment does not mean that it is actually used in the curriculum and therefore stresses the need to train teachers and improve technical infrastructure. Nevertheless, these recommendations seem to us to be too invested in technological determinism. Associating a digital environment with a training system obviously does not guarantee an automatic production of skills. More broadly, the use of digital technology in a course is not necessarily equivalent to pedagogical innovation. For example, the design of an e-learning course requires more than just the teacher’s command of ICT. The lessons provided must be reconfigured or they will be distorted.