The Economic and Labour Relations Review

Investigations into new technologies, employment and working conditions are timeless and consequently have occupied research, public policy, and popular fiction for centuries. However, in addition to the uncertainty created by the introduction of new technologies, the current coronavirus pandemic, with its associated impact on health and the economy, has led to increased volatility across the globe. The global medical crisis arising from the worldwide spread of COVID-19 is predicted to lead to a global economic crisis and subsequent deep depression. The resultant economic, social and political repercussions are likely to be felt for years or even decades to come, equalling the great depression of the last century. Consequently, it is difficult to make long-term accurate predictions about the impact of new technologies on industry, society, and labour. In this context, the aim of this introductory article to the themed volume is to consider the potential challenges and opportunities associated with the Fourth Industrial Revolution technologies and potential impacts on work and workplaces. This introductory article comprises an international collection of research that examines the impact of technological change on employment and working conditions with consideration given to the additional impacts of the COVID-19 crisis.

JEL Codes: O14, O33

This article addresses the unresolved question of whether recent technological change causes job instability in a non-western context. China is now the world’s largest user of industrial robots. A Lewis turning point has been predicted, involving a transition from a plentiful supply of rural low-cost workers to a labour shortage economy in which rising labour costs drive labour-technology substitution. The routine-biased technological change hypothesis suggests that technology-induced routinisation in job task content has a profound impact on employment structure. This study captures the extent of routinisation of jobs in the transitional context of China and examines the incidence and impact of routinisation on labour turnover in the labour market. Using rotating panel data from the China Labour-force Dynamics Survey 2012, 2014 and 2016, this study, based on individual information with regard to flexibility in work schedules and degree of autonomy in workload and task content on the job, follows a recently developed measure to construct a routine intensity index and indicates a division into three routine intensity groups. The empirical findings show that the probability of job mobility is significantly increased with the magnitude of routine task intensity, suggesting that the process of technology-induced routinisation is strongly associated with labour turnover.

JEL Codes: J63, J20

The race to develop and implement autonomous systems and artificial intelligence has challenged the responsiveness of governments in many areas and none more so than in the domain of labour market policy. This article draws upon a large survey of Singaporean employees and managers (N = 332) conducted in 2019 to examine the extent and ways in which artificial intelligence and autonomous technologies have begun impacting workplaces in Singapore. Our conclusions reiterate the need for government intervention to facilitate broad-based participation in the productivity benefits of fourth industrial revolution technologies while also offering re-designed social safety nets and employment protections.

JEL Codes: J88, K31, O38, M53

This study examines the causal relationship between education and the use of digital collaborative platforms as a first step in exploring the potential impact of the new digital labour markets on inequality. From the viewpoint of transaction costs theory, the less educated could benefit significantly from the digital collaborative economy due to the reduction in information costs made possible by this new form of exchange. Conversely, a positive relationship between educational level and platform use may be expected following neoclassical and institutionalist economic theories. Using microdata from the 2016 Eurobarometer survey, together with an instrumental variables strategy and conventional ordinary least squares models, hypothesis testing reveals that education has a clear positive effect on digital collaborative platform use. As a result, the less educated are less likely to access the job opportunities offered by digital labour markets. Understanding the relationship between education and access to digital collaborative platforms and impacts on socio-economic inequality is crucial for designing future public policies that promote social justice and well-being in a disrupted landscape.

JEL Codes: I24, J47, O34

While traditional labour market estimates indicate that there has been little change in the proportion of workers holding multiple jobs in North America, survey instrument deficiencies may be hiding more substantial growth driven by the gig economy. To address this possibility, I test a broader measure of multiple jobholding to examine its prevalence in the Canadian workforce based on two national studies of workers (2011 Canadian Work Stress and Health Study and 2019 Canadian Quality of Work and Economic Life Study). Almost 20% of workers in 2019 reported multiple jobholding – a rate that is three times higher than Statistics Canada estimates. While multivariate analyses reveal that the multiple jobholding rate in 2019 was 30% higher than in the 2011 Canadian Work Stress and Health Study, multiple jobholders in 2019 were less likely to report longer work hours in secondary employment. Analyses also revealed that having financial difficulties is consistently associated with multiple jobholding in 2011 and 2019. Collectively, these findings suggest that while the spread of short-term work arrangements has facilitated Canadians’ secondary employment decisions, for many workers these decisions may reflect underlying problems in the quality of primary employment in Canada, rather than labour market opportunity. I discuss the potential links between multiple jobholding, the gig economy and employment precariousness.

JEL Code: J21

Skills that are difficult to automate are expected to increase in demand and reward according to skill-biased technological change advocates, who have identified high rewards for cognitive and social skills. However, such broad skill categories involve numerous essential competencies that can be differentially rewarded or go simply unrewarded. Using US data, this article analyses the demand for and payment of linguistic competency, a cross-cutting kind of skill that is basic for both cognitive and social work in the new economy and is one of the human capacities that is most difficult to automate. While human capital theory predicts an increase in wages as the demand for linguistic skills rises, from cultural/institutional perspectives, it can be theorised that communicative abilities and foreign-language knowledge are socially undervalued because of their association with feminised activities, ethnicity, and low-status service jobs. We analyse the demand and reward for linguistic skills through a two-step analysis of occupational and individual data derived from two sources: the Occupational Information Network and the Current Population Survey. Results show that while ‘hard’ verbal-reasoning skills are associated with high average salaries, as is predicted by neoclassical theory, the potentially undervalued linguistic skills – interactive and multilingual skills – are unrewarded and even penalised. This evidence requires further political attention, given its implications for large number of workers, especially in feminised, low-status service jobs.

JEL Codes: J01, J23, J24, J31, J38

With economic reform, in China, labour turnover of seafarers became more possible. However, little attention has been paid to its consequences. A limited literature indicates that Chinese seafarers may leave state-owned enterprises to become freelance seafarers, working in the global labour market for better wages and employment conditions. There have been predictions of a substantial increase in seafarer export, with China becoming the top labour supplier to the global maritime industry. However, such expectations have been largely unmet. Through 157 qualitative interviews with seafarers and managers in Chinese ship crewing agencies, we explore some reasons why this may be so. The findings suggest that Chinese seafarers are in fact limited in their willingness and ability to leave their companies. This is due to a complex mixture of organisational, regulatory, infrastructural and personal contexts that are their everyday experience of work in China. Analysis further suggests that the underdevelopment of a national regulatory infrastructure and welfare support mechanism for seafarers, along with poor implementation of the Maritime Labour Convention 2006, combine to limit the extent of the reform of the Chinese seafaring labour market. Together, these factors help to explain why China’s seafaring labour export has been far lower than anticipated.

JEL Codes: D40, E24, F66, J61, J83

Human civilisation faces a series of existential threats from the combination of five global and human-engineered challenges, namely climate change, resource depletion, environmental degradation, overpopulation and rising social inequality. These challenges are arguably being manifested in both an increased likelihood and magnified impact of catastrophes like forest fires, prolonged droughts, pandemics and social dislocation/upheaval. This article argues that in understanding and addressing these challenges, important lessons can be drawn from what has repeatedly caused organisational failures. It applies the ‘Ten Pathways to Disaster’ model to a series of disasters/catastrophic events and then argues this model is salient to understanding inadequate responses to the five threats to civilisation. The article argues that because these challenges interact in mutually reinforcing ways, it is critical to address them simultaneously not in isolation.

JEL Codes: H12, I14, I31, J11, Q01