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Digital transformation, big data, and the future of work

Digital technologies have rapidly been assimilated into our everyday lives, for instance via digital payment systems and the widespread diffusion of broadband infrastructure. But what effect is digitalization having on the world of work? How is it changing job design and influencing the nature of employment in different areas of the world? What role can and should different types of data (e.g. “Big Data,” Google search activity data, and molecular genetic data) play in decision making in labor markets and our future societies? Who will be the entrepreneurs of the future who will innovate to transform ideas and knowledge into new products and services? Will the “gig economy” and other non-traditional work relationships continue to grow in prominence? Will robots really take all our jobs? Answering these questions and finding a solution to how we plug the inevitable skills gap between digital illiterates and digital natives will provide policymakers with many interesting challenges in the years to come.

  • Digital leadership: Motivating online workers

    Which leadership techniques and tools should digital leaders use to communicate effectively with remote teams and gig workers?

    Petra Nieken, September 2022
    Remote work and digital collaborations are prevalent in the business world and many employees use digital communication tools routinely in their jobs. Communication shifts from face-to-face meetings to asynchronous formats using text, audio, or video messages. This shift leads to a reduction of information and signals leaders can send and receive. Do classical leadership and communication techniques such as transformational or charismatic leadership signaling still work in those online settings or do leaders have to rely on transactional leadership techniques such as contingent reward and punishment tools in the remote setting?
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  • How is new technology changing job design? Updated

    Machines’ ability to perform cognitive, physical, and social tasks is advancing, dramatically changing jobs and labor markets

    The IT revolution has had dramatic effects on jobs and the labor market. Many routine manual and cognitive tasks have been automated, replacing workers. By contrast, new technologies complement and create new non-routine cognitive and social tasks, making work in such tasks more productive, and creating new jobs. This has polarized labor markets: while low-skill jobs stagnated, there are fewer and lower-paid jobs for middle-skill workers, and higher pay for high-skill workers, increasing wage inequality. Advances in AI may accelerate computers’ ability to perform cognitive tasks, heightening concerns about future automation of even high-skill jobs.
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  • Does employee ownership improve performance? Updated

    Employee ownership generally increases firm performance and worker outcomes

    Douglas Kruse, May 2022
    Employee ownership has attracted growing attention for its potential to improve economic outcomes for companies, workers, and the economy in general, and help reduce inequality. Over 100 studies across many countries indicate that employee ownership is generally linked to better productivity, pay, job stability, and firm survival—though the effects are dispersed and causation is difficult to firmly establish. Free-riding often appears to be overcome by worker co-monitoring and reciprocity. Financial risk is an important concern but is generally minimized by higher pay and job stability among employee owners.
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  • Impacts of regulation on eco-innovation and job creation Updated

    Do regulation-induced environmental innovations affect employment?

    Jens Horbach, November 2020
    New environmental technologies (environmental/eco-innovations) are often regarded as potential job creators—in addition to their positive effects on the environment. Environmental regulation may induce innovations that are accompanied by positive growth and employment effects. Recent empirical analyses show that the introduction of cleaner process innovations, rather than product-based ones, may also lead to higher employment. The rationale is that cleaner technologies lead to cost savings, which helps to improve firms’ competitiveness, thereby inducing positive effects on their market shares.
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  • The gig economy

    Non-traditional employment is a great opportunity for many, but it won’t replace traditional employment

    Paul Oyer, January 2020
    The number of people holding non-traditional jobs (independent contractors, temporary workers, “gig” workers) has grown steadily as technology increasingly enables short-term labor contracting and fixed employment costs continue to rise. For many firms that need less than a full-time person for short-term work and for many workers who value flexibility this has created a great deal of surplus. During slack economic periods, non-traditional work also serves as an alternative safety net. Non-traditional jobs will continue to become more common, though policy changes could slow or accelerate the trend.
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  • Big Data in economics

    New sources of data create challenges that may require new skills

    Big Data refers to data sets of much larger size, higher frequency, and often more personalized information. Examples include data collected by smart sensors in homes or aggregation of tweets on Twitter. In small data sets, traditional econometric methods tend to outperform more complex techniques. In large data sets, however, machine learning methods shine. New analytic approaches are needed to make the most of Big Data in economics. Researchers and policymakers should thus pay close attention to recent developments in machine learning techniques if they want to fully take advantage of these new sources of Big Data.
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