Work organisation and job quality in the digital age

‘Work organisation’ refers to the division, coordination and control of work to fulfil the goals of an organisation. It includes the tasks that need to be performed, their assignment and management, the processes of production and service delivery, and the interaction among workers, including managers, within and across functional units in the organisation.

Work organisation is influenced by the business model of an organisation and in turn affects the working conditions and job quality of staff, for example as regards their autonomy and flexibility or the job satisfaction derived from different approaches to cooperation in the organisation or scheduling of tasks. As some elements of working conditions (such as working time) are regulated by legislation and collective agreements, the design and implementation of work organisation is not always at the full discretion of the employer but also a result of social dialogue and employee participation.

A full list of references used to compile this research digest can be found at the end of the page. 

Author: Irene Mandl

 

Overview

 


 

 

Policy pointers

  • Policy should ensure that managers are familiar with the changes in work organisation driven by digitalisation and their impact on workers. They should be supported in establishing human resource management and other workplace practices that result in ‘win–win’ situations for employees and the business, for example through exchange of good practices and management training.

  • Policy should encourage organisations to make the most of the potential of automation and digitisation technologies to increase the efficiency of work organisation and workflows, for example through exchange of good practices or the provision of advice and consultancy.

  • Particular attention should be devoted to organising work in an automated environment in such a way as to limit physical and psychosocial risks, including the isolation of workers. In the digitised workplace, workplace practices leading to enhanced teamwork (multidisciplinary and cross-organisational) should take into account that this type of work organisation does not suit all workers, and alternative tasks should be identified for them.

  • Organisations applying data-driven work organisation, notably related to digitisation technologies, should be made aware of and supported to meet the challenge of finding a balance between using data to improve business processes and the work environment and respecting workers’ data ownership and privacy.

  • Algorithmic matching of supply of and demand for paid labour – as in platform work – provides opportunities for effective and efficient task assignment. However, policymakers could engage to ensure that algorithms are more transparent and that dependency on algorithms is reduced if they are not yet fully developed. Safety nets should be established with regard to algorithmic management, including when it occurs in traditional employment relationships.

 


Digitalisation: General and comparative perspectives

Introduction

As digitalisation has the potential to affect business models and the task composition of jobs, it also influences how work is assigned, managed, coordinated and controlled within and across organisations. In this context, the issues most commonly discussed relate to the generation, ownership and use of data (including for monitoring and surveillance of employees and their performance) and to the assignment, management and monitoring of tasks with the assistance of algorithms and artificial intelligence.

However, digitalisation also affects more traditional elements of work organisation. Most recently, and as a result of the restrictions imposed in response to the COVID-19 pandemic, awareness of the interlinkages between place of work and digitalisation has increased because of the surge in remote work/telework. Before the crisis, there were considerable differences across Europe as regards employees’ opportunities to work remotely. Eurostat data from 2016 show that the share of enterprises providing their staff with remote access to emails, documents or applications ranged from more than 80% in Sweden, Slovenia, Cyprus and Finland to less than 30% in Romania (Figure 1).

Figure 1: Shares of enterprises providing employees with remote access to the enterprise’s email system, documents or applications, EU27 and the UK, 2016 (%)

In flexible workplaces, but not exclusively in them, digitalisation has been found to impact on working time. On the one hand, this refers to the duration – shorter or longer – of working hours. On the other hand, working time schedules and patterns can be affected (for example, changes in shifts or on-call/on-demand arrangements).

The European Company Survey (ECS) 2019, conducted by the European Centre for the Development of Vocational Training (Cedefop) and Eurofound among almost 22,000 establishments with at least 10 employees, distinguishes between four types of establishments based on the extent to which they have adopted digital technologies. It found that, while in half of ‘highly digitalised’ establishments at least 60% of staff can organise their working time and schedule their tasks independently, this is the case in only about one-fifth of establishments with ‘limited digitalisation’ (Figure 2).

Figure 2: Shares of employees who can organise their working time and schedule their tasks independently by digitalisation intensity of establishments, EU27 and the UK, 2019 (%)

Owing to changes in the products and services offered, in the processes of production and service provision or in the task composition of jobs, workers may be required to adapt how they align and coordinate their work with that of others. Teamwork within the functional unit and across the organisation may increase or decrease and involve elements such as enhanced human–machine interaction or virtual cooperation using cloud solutions.

The ECS 2019 found that teamwork is much more prevalent in highly digitalised establishments (84%) than in those with limited digitalisation (55%) (Figure 3).

Figure 3: Presence of teamwork by digitalisation intensity of establishments, EU27 and the UK, 2019 (%)

Notes: See Figure 1 notes.

Furthermore, some digital technologies trigger more cooperation with other organisations, resulting in changes in work organisation along the supply chain and altered coordination with external business partners.

Finally, management practices – for example how managers communicate and interact with their teams, monitor tasks and employee performance, and make business decisions – can be impacted by digitalisation. Data from the ECS 2019 indicate the higher prevalence of a corporate culture in which managers allow their staff to carry out their work autonomously in highly digitalised establishments (84%) than in those with limited digitalisation (65%) (Figure 4).

Figure 4: Management approach by digitalisation intensity of establishments, EU27 and the UK, 2019 (%)

Notes: See Figure 1 notes.

Work organisation, and related human resource management and workplace practices, show a clear association with establishment performance and workplace well-being. The ECS 2019 found a clear positive association between establishment performance, workplace well-being and the digitalisation intensity of the establishment – although it is not possible to establish the direction of causality. The ‘high investment, high involvement’ category is most prevalent among highly digitalised establishments (33%) and least prevalent among those with limited digitalisation (9%) (Figure 5). In these establishments, employees have a high degree of autonomy, are often offered incentives and variable pay, are often offered training and learning opportunities and tend to be involved in decision-making. This category of establishment scores best in terms of workplace well-being and establishment performance. At the other end of the spectrum is the ‘low investment, low involvement’ category, characterised by the lowest scores for establishment performance and workplace well-being. This category is most prevalent among establishments with limited digitalisation (34%) and least prevalent among those that are highly digitalised (9%). Establishments in this category offer employees little autonomy, do not make much use of non-monetary incentives or variable pay, and offer limited opportunities for learning or involvement in decision-making.

 

Figure 5: Bundles of workplace practices in establishments by digitalisation intensity, EU27 and the UK, 2019 (%)

 

Notes: See Figure 1 notes.

 

Opportunities

  • Reduced work intensity and working time
  • More efficient workflows
  • Less physical strain and mental stress
  • Enhanced teamwork and improved cooperation within and across organisations

Automation and digitisation can result in changes in work organisation measures intended to tackle skills and human resources shortages (for example, by replacing human input with machine input or involving a remote workforce), which can be advantageous for employees, as it can result in reduced work intensity and working time.

Furthermore, technologies can be used to make work organisation and workflows more efficient, physically less demanding or mentally less stressful for workers, thus contributing to improved working conditions and job quality. They can also act as early warning tools, resulting in adjustments to workload or workflows to the benefit of workers.

The expected increase in teamwork and cross-organisational cooperation, as well as the greater autonomy and flexibility that some workers experience as a result of digitalisation, can improve not only individuals’ working conditions and job satisfaction but also the overall corporate culture and staff commitment, resulting in a higher likelihood of ‘win–win’ workplace practices, benefiting both the employees and the business.

Risks

  • Physical and psychosocial risks
  • Unfavourable remotely dispersed workflows and coordination/information challenges
  • Decreasing job satisfaction due to management and workplace practices that do not fit with the preferences of the workers

Work organisation drawing on a combination of human input and advanced technologies entails physical and psychosocial risks for the affected employees. Physical risks can emerge when the digital workplace – whether it is at the employer’s premises or a remote location – does not meet the required standards, when traditional standards are not fit for purpose for the digital work environment, or when workers are not adequately informed about and trained in how to deal with digital technologies. Psychosocial risks emerge when employees lack the skills required to carry out the (new or changed) tasks assigned to them, when workload and work intensity increase, when new forms of surveillance are introduced or when there is a perceived or actual requirement to be always connected.

Remotely dispersed workflows can result in challenges as regards coordination among workers and issues related to information flows (information overload as well as lack of required information).

Management and workplace practices driven by digitalisation – such as enhanced cooperation within and across the organisation and greater autonomy for some workers while for others discretion is substantially reduced – can result in friction in the workplace as well as reduced job satisfaction among workers whom this type of work organisation does not suit.

Concluding commentary

Digitalisation provides opportunities to make work organisation and workflows more efficient and effective, which in turn can benefit employees as a result of lower work intensity, improved working time conditions, less physical and psychosocial strain, better cooperation within and across organisations or more autonomy and flexibility. However, it can also have the opposite effect if workers are not well equipped for a digital workplace in terms of skills or information on how to handle technologies and workflows. Furthermore, if human resource management and other workplace practices are applied in such a way as to reap the benefits of digitalisation for the organisation, but to the detriment of the workers, there is the risk that the efforts made in recent decades to improve working conditions and job quality in Europe will be reversed.

As work organisation is largely at the discretion of the employer, potential policy interventions are somewhat limited. However, legislation can indirectly influence some elements, for example through working time regulation, health and safety requirements, data protection rules or information and consultation procedures. This last example flags up the potential role of social dialogue and collective bargaining at national, sectoral and workplace levels, which might be able to more directly influence work organisation. Finally, policy could intervene through ‘soft measures’, such as providing information to and facilitating exchange of good practices among managers, staff and their representatives or supporting management training to equip business leaders with the skills required to organise a workplace in the digital age.

 


Automation

Automation is one of the ‘vectors of change’ identified as part of the broader notion of ‘digitalisation’ in Eurofound’s conceptual framework. It is the replacement of human input, in full or in part, by machine or software input. Advanced robotics, both for services and for manufacturing, is grouped with autonomous vehicles under the automation vector, since the ultimate aim of their application is to substitute machine for human input.

Introduction

Work organisation influences which specific tasks can be automated in an organisation. If work is organised in a way that reduces the importance of key human labour attributes by centralising, standardising and breaking down tasks, the possibilities for automation are high and can include algorithmic decision-making, for example for task assignment.

Data from Eurofound’s European Working Conditions Survey suggest that in the past 20 years, standardisation has increased considerably, including in high-skilled occupations, such as professionals and managers, which previously were considered at less risk of automation. Advanced robotics in particular is expected to affect workplace practices and people management as a result of the complexities of human–machine interaction, which may result in more extensive supervision needs (of the human–machine interaction and of the robots involved; the supervision may also be conducted by robots).

Increased automation is expected to result in more remote working, as advanced robotics can increasingly be operated remotely. In manufacturing (and in some services sectors, such as logistics or transport), automation can also affect the time component of work organisation. As production times are likely to increase, in extreme cases to 24/7, shift work or flexitime models will be required for those working with or supervising the technology. Both elements – the spatial and the time components of work organisation – are in turn likely to affect information, communication and coordination processes in organisations.

Automation not only results in changes in work organisation due to the replacement of humans by machines. Integrating robots into an existing work system also requires a review of processes to ensure that the cooperation between humans and machines is effective and efficient, as well as safe for the workers. The capabilities of employees as well as expectations of clients need to be taken into consideration in this review. Previous research highlights the need for the following considerations to be taken into account when designing work organisation linked to automation:

  • which tasks are to be performed by humans in combination with the automated system
  • how the automated system fits into the organisation’s business model and workplace practices (for example, organisational structure, training and recruitment, division of labour, cooperation)
  • how the automated system translates into hardware and software needs
  • whether there is a need to adapt the physical work environment (for example, space to accommodate the machines, separating the robots’ workspace from that of humans, structuring the workspace to make the deployment of the robots effective).

After its adoption, automation can be used strategically to improve work organisation and workflows by analysing the data generated by robots and other automation technology.

Opportunities

  • Modernisation of work organisation and workflows
  • Reduction in repetitive tasks and physical strain
  • Job enrichment
  • Greater autonomy as regards time and place of work

Automation technologies tend to drive modernisation of factories and production lines, which has the potential to result in positive changes to work organisation and working conditions. They can reduce repetitive tasks (and hence job strain), facilitate job enrichment and allow for greater working time autonomy. As physically demanding tasks can be conducted by machines, strain on workers is reduced, and there may be a lower incidence of accidents and injuries.

The introduction of automation technologies may result in efficiency gains and smoother work processes, and more opportunities to work remotely for staff supervising the machines.

Risks

  • Fragmentation of jobs into tasks, which can make organisation, coordination and communication more difficult
  • Contractual instability
  • Limited autonomy
  • Less perceived meaningfulness of work
  • Physical and psychosocial risks
  • A less social work environment

Automation contributes to the fragmentation of jobs into tasks, which creates challenges for work organisation in terms of the need to ensure uninterrupted workflows as well as coordination and communication among teams (and between humans and machines). Job quality may decrease as a result of increased contractual instability, the perception of performing less meaningful work due to the loss of the bigger picture, or more limited autonomy because workers have to fit into the rigid workflow required by the automated system.

Interaction with robots can give rise to accidents and hence physical risks for workers, notably if they, or their managers, are not adequately informed about potential hazards and trained in working with the technology. Psychosocial risks can emerge in the form of increased stress if work intensity or pace of work is determined by a machine, or if the data generated by the technology are used for employee monitoring and surveillance.

The work environment may become less social when automation technologies are introduced, for example because tasks are carried out in isolation (or with the machine instead of a human co-worker) or because of increased remote working.

Working time quality may decrease owing to 24/7 shifts, or on-call time to ensure that maintenance and repair of the automation technology is done in a timely manner.

Concluding commentary

Automation offers the potential to improve work organisation and workflows by modernising them and making them more effective and efficient, which can be beneficial for the job quality of workers. Physically demanding or repetitive tasks can be automated, thus reducing employees’ exposure to physical and psychosocial risks. Increased opportunities for remote working and greater working time flexibility may be other positive outcomes for the workforce.

However, these opportunities can entail risks if management and workers are not made aware of the possible effects of automation or if automation technologies are deployed without taking a human-centric approach. Policy could support the exchange of good practices and the provision of advice and consultancy as regards the design and implementation of work organisation and workflows in an automated environment. Managers and workers need to be trained on how to handle automation technologies, how to deal with related processes and how to interact in and with hybrid teams.

Policy needs to ensure that the data generated by automation technologies are effectively used to improve work organisation while at the same time making sure that they are not exploited to the disadvantage of workers, for example through intrusive employee performance monitoring.

Worker representatives, social dialogue and collective bargaining should have a specific role in the design and implementation of automation technologies in the workplace to ensure decent work organisation and working conditions.

 


Digitisation

Digitisation is one of the ‘vectors of change’ forming part of ‘digitalisation’ in Eurofound’s conceptual framework. It refers to the process through which aspects of the physical world are rendered into data and virtual models, and vice versa. Three main technologies fall under this vector of change, namely 3D printing, augmented and virtual reality (AR/VR) and the internet of things (IoT).

Introduction

Digitised workplaces by their nature involve work organisation characterised by cooperation across organisational functions, across organisations and with customers. Case studies on IoT and AR/VR find that access to the real-time data generated by the technology increases teamwork within and across organisational departments (see case studies of SanminaTTI Algeciras and Bosch Rexroth). Interaction and communication between different actors in the production/service provision processes intensifies, including in cases where those actors are geographically dispersed, and decision-making tends to involve a wider range of stakeholders. Similarly, increased cooperation can be observed when 3D printing is deployed, as design, material and process engineering, process operations and post-processing need to be linked and aligned.

Furthermore, digitisation has the potential to increase the incidence of remote working, as digitised processes are less place-bound than more traditional ones.

Digitised work organisation is data driven. What this means in practice depends very much on the specific technology deployed in the workplace. On the one hand, the data underlying and created by digitisation technologies can be used to revise work organisation and workflows, with the aim of optimising them (this might be expected, for example, where IoT is used). On the other hand, the data can become an integrated feature of work organisation, for example where tasks are assigned using technology (this might be expected, for example, where AR/VR is used). Related to the latter is the potential for digitisation technologies to be used for employee monitoring and control, as they facilitate the collection and use of fine-grained information about workers’ activities in and beyond the employer’s premises.

Opportunities

  • More effective and efficient workflows
  • Improved communication and information flows
  • Employment and job opportunities and job enrichment for those workers who prefer (multidisciplinary) cooperation
  • Remote working
  • Improved safety at work

Data-based work organisation can result in more effective and efficient workflows that benefit both workers (for example, through smoother and more clearly defined processes that may also result in reduced workload, or by facilitating quicker and more effective communication) and companies (for example, through higher productivity or lower costs). IoT, for instance, has been observed to result in less paper-based work environments, quicker decision-making and better planning, for example, with regard to workload and shifts (see case studies on Centro Seia and Bosch Rexroth. This increases organisational efficiency but also benefits workers, as the work environment becomes more predictable and less time is spent in situations where work is pending or uncertain.

Digitisation technologies have the potential to improve communication and information flows, and thus teamwork. Enhanced collaboration within and across organisations provides good employment and job opportunities as well as job satisfaction for those workers who derive pleasure from networking and cooperation. Multidisciplinary cooperation in particular is likely to increase as a result of digitisation, and this could result in job enrichment for some occupational profiles, as well as in a competitive advantage both for individual workers in the labour market (who will gain specific skills) and for companies/supply chains in national or global product/services markets (which will be able to offer improved product/service quality).

The possibility of remote working can be beneficial for some types of workers, such as those who are more place-bound (for example, because of care responsibilities or limited mobility) or those living in remote areas.

Digitisation technologies, notably IoT and AR/VR, can also be used to improve workers’ physical and psychosocial safety, by exploiting their capacity to monitor the work environment and detect potential hazards early on.

Risks

  • Constant and intrusive employee monitoring and surveillance, resulting in negative psychosocial effects and deteriorating employee–employer relationships
  • Reduced autonomy of workers due to data-driven work organisation
  • Low job quality for workers challenged by (multidisciplinary and cross-organisational) teamwork

The potential that digitisation technologies, notably IoT, offer for constant monitoring of workers poses challenges to worker autonomy and privacy/data protection, as employers could implement intrusive surveillance practices. This, in turn, could result in negative psychosocial effects for workers, who are (or feel that they are) permanently monitored, resulting in stress, higher work intensity and longer working hours, and also a loss of trust in management and less commitment to work.

Data-driven work organisation, particularly related to IoT, also has the potential to reduce workers’ autonomy and discretion by setting up rigid workflows in which workers receive instructions from the technology application that need to be strictly followed. Such digitised workflows can create a feeling of alienation in workers.

The expected higher prevalence of teamwork in digitised work organisations could negatively affect job quality for those workers who find collaboration with others challenging, particularly if such cooperation is multidisciplinary and across organisations.

Concluding commentary

Digitisation is based on the generation and use of data. This key feature impacts work organisation. As processes are brought into the digital sphere, multidisciplinary and cross-organisational cooperation becomes more important, as do data-driven workflows. This offers opportunities for workers who are keen on teamwork and remote working, as well as for employers in terms of optimising processes and procedures.

On the other hand, it also poses a risk to those workers who feel challenged by this type of work organisation, those affected by reduced autonomy due to inflexible standardised processes and those subject to (more intrusive) surveillance practices.

As of mid-2021, there was not much evidence that employers were, as a matter of course, (mis)using the data generated by digitisation technologies to the disadvantage of employees. Data analytics tend to be used to improve business processes rather than for employee monitoring purposes. However, as the prevalence of digitisation technologies spreads, there is some likelihood that they may be used for purposes beyond those for which they were initially deployed, including for performance monitoring of employees. Policymakers should take care to ensure that work organisation in the digitised workplace – including data-driven task assignment, workflows and monitoring practices – is designed to benefit both employers and employees. Awareness raising and the fostering of leadership competencies (to support interdisciplinary thinking and working) among managers form an important first step, which should be followed by regulation through legislation and collective bargaining.

 


Platforms

Platform work is a form of employment in which organisations or individuals use an online platform to access other organisations or individuals to solve problems or provide services in exchange for payment.

Introduction

The key feature of work organisation in platform work is the algorithmic matching of supply of and demand for paid labour. Workers use online platforms or apps to offer their services or search for clients; clients use the technology to list the tasks they want done or search for service providers; and the algorithm underlying the online platform or app facilitates the process of bringing the two parties together. In general, the platform economy is also characterised by rating mechanisms, through which workers (and sometimes also clients) are assessed, either manually by the client (or worker) or algorithmically through the platform. Ratings tend to affect the next matching process – that is, they influence the probability that a worker will be offered tasks.

There is a substantial variation in platform work. In some types of platform work, platforms go beyond matching activities, and also get involved in managing the performance of the task, prescribing (some elements of) work organisation, such as scheduling of tasks or workflows. As algorithms are at the core of business models in the platform economy, the work organisation approach used by platforms tends also to rely on algorithmic management.

While platform work is still small in scale, it has been growing dynamically in scale and scope during the past 15 years. Accordingly, experts expect further growth in this business model and form of employment; they also expect that it will spread as a form of work organisation into the traditional economy. In other words, employers in the offline economy will increasingly use platforms to outsource individual tasks, or use algorithmic task assignment and management for their internal staff.

Opportunities

  • Flexibility for workers and clients
  • Effectiveness and efficiency of algorithmic matching
  • Discretion for workers on how to organise work on tasks

The most commonly cited opportunity presented by platform work is the inherent flexibility for both workers and clients as regards the performance of tasks. As there is, in most cases, no continuous employment relationship among the three parties involved (platform, worker and client), services and tasks can be offered as needed/preferred, at short notice and literally without any commitment until agreement on a specific task has been reached. This makes it attractive for clients (as does the low cost involved) and for some types of workers, who do not want to or cannot commit to more rigid work organisation.

Algorithmic matching is said to be efficient and effective and, if well programmed, more objective than task assignment by humans, as stereotyping and selection bias can be eliminated. This is particularly advantageous for vulnerable groups in the labour market, as it can facilitate their access to work and hence income.

Some types of platform work, notably those related to medium- to high-skilled and larger tasks, provide workers with a high degree of discretion in how they organise their work, including with regard to processes and working time.

Risks

  • Deficiencies in algorithmic task assignment and rating mechanisms
  • Lack of transparency of algorithms
  • Mismatch between employment status and algorithmic management
  • Employment and income insecurity, unpredictability of work, limited social protection
  • Spillover of algorithmic management into traditional employment relationships

While, in theory, algorithmic matching has the potential to result in neutral task assignment, as of mid-2021 anecdotal evidence hinted that the underlying algorithms in many cases were not yet fully developed, so that task assignment was not as objective as might be expected, with discrimination (for example, on the basis of gender or ethnicity) even occurring.

As the mechanism of the algorithm tends not to be transparent to the workers, they have a limited ability to make their case if they feel unfairly treated in the context of task assignment or ratings.

Risks for workers engaged in platform work become particularly obvious when algorithmic work organisation is used not only for matching but also to manage how tasks are performed. As the majority of platform workers are considered to provide their services as self-employed workers, the platform’s (algorithmic) interference in work organisation gives rise to the question of whether such classification of their employment status is appropriate or, rather, results in a situation in which workers’ rights and entitlements are unfairly curtailed.

Irrespective of employment status, the fact that platform-based work organisation deals with the matching of individual tasks (unlike work organisation in a traditional job, understood as a bundle of tasks) results in employment and income insecurity, limited predictability of work, limited social protection and lack of career prospects. Furthermore, the particularities of work organisation in some types of platform work can result in limited autonomy and flexibility, high work intensity and unfavourable working time (unsocial hours, unpaid working time, 24/7 availability).

Algorithmic management, as ‘tested’ in platform work, has started to spill over into the traditional economy. This provides employers with new tools to exercise power in labour relations through control and surveillance.

Concluding commentary

Algorithmic matching of supply of and demand for labour is an innovative element of work organisation. Its potential should be further explored as regards gains related to effectiveness and efficiency. However, full reliance on algorithms is risky, as they do not yet seem fully technologically developed, and their deficiencies can have detrimental effects on workers’ access to work.

Algorithmic management, as ‘tested’ in platform work but spilling over into traditional employment relationships, raises concerns regarding the power relationship between the parties involved and the resulting effects on the employment and working conditions of workers. Policymakers could in particular engage in increasing the transparency of the mechanisms of algorithms and in providing workers with options for seeking redress if they feel unfairly treated.

Legislating the platform economy is challenging because of its particularities; difficulties also arise when representing and mobilising platform workers. Nevertheless, regulatory safety nets are required, and joint approaches, combining the competencies of governments, social partners and grassroots organisations, may be the most promising methods.

Related material

Related policy pointers Related research digests

 


References

Eurofound sources

Eurofound (2018), Additive manufacturing: A layered revolution , Eurofound working paper, Dublin.

Eurofound (2018), Advanced industrial robotics: Taking human-robot collaboration to the next level , Eurofound working paper, Dublin.

Eurofound (2018, updated 2019), Employment and working conditions of selected types of platform work , Publications Office of the European Union, Luxembourg.

Eurofound (2018), Industrial internet of things: Digitisation, value networks and changes in work , Eurofound working paper, Dublin.

Eurofound (2019), Advanced robotics: Implications of game-changing technologies in the services sector in Europe , Eurofound working paper, Dublin.

Eurofound (2019), Platform work: Maximising the potential while safeguarding standards Publications Office of the European Union, Luxembourg.

Eurofound (2019), Virtual and augmented reality: Implications of game-changing technologies in the services sector in Europe , Eurofound working paper, Dublin.

Eurofound (2019), Wearable devices: Implications of game-changing technologies in services in Europe , Eurofound working paper, Dublin.

Eurofound (2020), Employee monitoring and surveillance: The challenges of digitalisation , Publications Office of the European Union, Luxembourg.

Eurofound (2020), Game-changing technologies: Transforming production and employment in Europ , Publications Office of the European Union, Luxembourg.

Eurofound (2021), Job quality , web page, accessed 22 September 2021.

Eurofound (2021), Working conditions , web page, accessed 22 September 2021.

Eurofound (2021), Work organisation , web page, accessed 22 September 2021.

Eurofound (forthcoming), Digitisation in the workplace: Uptake, drivers and impact on work organisation and job quality , Publications Office of the European Union, Luxembourg.

Eurofound and Cedefop (European Centre for the Development of Vocational Training) (2020), European Company Survey 2019: Workplace practices unlocking employee potential , European Company Survey 2019 series, Publications Office of the European Union, Luxembourg.

European Union and Eurofound (2019), How computerisation is transforming jobs: Evidence from Eurofound’s European Working Conditions Survey , European Commission, Seville.

Other sources

Acatech and Forschungsunion (2013), Securing the future of German manufacturing industry: Recommendations for implementing the strategic initiative INDUSTRIE 4.0 , Plattform Industrie 4.0, Frankfurt.

Aloisi, A. (2016), ‘ Commoditized workers: Case study research on labor law issues arising from a set of “on-demand/gig economy” platforms ’, Comparative Labor Law & Policy Journal, Vol. 37, No. 3, pp. 653–690.

Brettel, M., Friederichsen, N., Keller, M. and Rosenberg, M. (2014), ‘How virtualization, decentralization and network building change the manufacturing landscape: An Industry 4.0 perspective ’, International Journal of Mechanical, Aerospace, Industrial, Mechatronics and Manufacturing Engineering , Vol. 8, No. 1, pp. 37–44.

Datcu, D., Lukosch, S., Lukosch, H. and Cidota, M. (2015), ‘ Using augmented reality for supporting information exchange in teams from the security domain ’, Security Informatics, Vol. 4, No. 1.

Decker, M., Fischer, M. and Ott, I. (2017), ‘ Service robotics and human labor: A first technology assessment of substitution and cooperation ’, Robotics and Autonomous Systems, Vol. 87, pp. 348–354.

Dellea, D., Vogel, S., Meletiadis, I., Gupta, N., Zahn, F., Görgülü, K. et al (2016), Football’s digital transformation: Growth opportunities for football clubs in the digital age , PwC.

Financial Times (2017), ‘ The impact of cobots on workers’ wellbeing ’, 13 September.

Fischer, M. (2012), ‘ Interdisciplinary technology assessment of service robots: The psychological/work science perspective ’, Poiesis Prax, Vol. 9, Nos. 3–4, pp. 231–248.

Gans, E., Roberts, D., Bennett, M., Towles, H., Menozzi, A., Cook, J. et al (2015), ‘Augmented reality technology for day/night situational awareness for the dismounted soldier’, in Proceedings Vol. 9470: Display Technologies and Applications for Defense, Security, and Avionics IX; and Head- and Helmet-Mounted Displays XX, International Society for Optics and Photonics, Bellingham, Washington, p. 947004.

Gross, H. M., Boehme, H., Schroeter, C., Müller, S., König, A., Einhorn, E. et al (2009), ‘ TOOMAS: Interactive shopping guide robots in everyday use – Final implementation and experiences from long-term field trials ’, in Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems , IEEE Press, St. Louis, Missouri, pp. 2005–2012.

International Federation of Robotics (2018), Robots and the workplace of the future , Frankfurt.

McKinsey Global Institute (2015), The internet of things: Mapping the value beyond the hype , (PDF) Toronto.

Probst, L., Frideres, L., Pedersen, B. and Caputi, C., PwC Luxembourg (2015), Service innovation for smart industry: Human-robot collaboration , Publications Office of the European Union, Luxembourg.

Robohub (2015), The state of telepresence: Healthcare and telemedicine , web page, accessed 22 September 2021.

Sundararajan, A. (2016), The sharing economy: The end of employment and the rise of crowd-based capitalism , MIT Press, Cambridge, Massachusetts.

The Conversation (2017), Why the rise of wearable tech to monitor employees is worrying , web page, accessed 22 September 2021.

The Newsroom (2015), Enter the smart warehouse , web page, accessed 22 September 2021.

Vandaele, K. (2019), Will trade unions survive in the platform economy? Emerging patterns of platform workers’ collective voice and representation in Europe , Working Paper 2018.05, European Trade Union Institute, Brussels.

Wang, H. (2015), ‘ Detection and alleviation of driving fatigue based on EMG and EMS/EEG using wearable sensor ’, in Proceedings of the 5th EAI International Conference on Wireless Mobile Communication and Healthcare , Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Brussels, pp. 155–157.

Wisskerchen, G., Thibault Biacabe, B., Bormann, U., Muntz, A., Niehaus, G., Jiménez Soler, G. and von Brauchitsch, B. (2017), Artificial intelligence and robotics and their impact on the workplace , IBA Global Employment Institute, London.

Wobbe, W., Bova, E. and Dragomirescu-Gaina, C. (eds.) (2016), The digital economy and the single market , Foundation for European Progressive Studies, Brussels.

Yang, H., Yu, J., Zo, H. and Choi, M. (2016), ‘User acceptance of wearable devices’, Telematics and Informatics, Vol. 33, No. 2, pp. 256–269.

 

 

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