Digitalisation and the generation left behind

Since the early 2000s, digitalisation has always been a trending phenomenon in economies around the world. From heavy machinery commonly seen in standardised production processes to the high-tech service AI used in hospitality and tourism industries, digitalisation is unarguably leading to changes in society and business in both the near and long-term future

Naturally, skill biases in the labour market have become a direct consequence of technological advancement. While the tech-savvy labourers can utilise technologies to improve their production efficiency, the unskilled positions such as hotel check-in staff, travel agents and restaurant waiters are in danger of being replaced by a robot

It is therefore clear that workers who entered the workforce before the technology boom are the most disadvantaged. Several past researchers have identified the need for those workers to acquire new technology-related skills to obtain a new job

However, retraining and upskilling the older, unskilled workers can be difficult in a capital market without policy intervention. 

Charness stated that it is usually more time-consuming for older workers to complete a training program. And upon completion of the program, older workers tend to receive a lower grade in performance evaluation than their younger co-workers. Desjardins and Warnke’s suggestion that aging is negatively associated with fluid intelligence, speed and logical reasoning provides an explanation to Charness’s earlier findings. This undoubtedly renders training older workers a more costly investment for firms than training younger workers. While providing adequate training to older workers improves their work efficiency and prevents job losses, it is often not in the firm’s best interest to voluntarily provide such an opportunity to their employees. Consequently, the supply of firm-sponsored training for older workers is clearly below an optimal level from society’s perspective. 

On the other hand, some may think that if firm-sponsored training doesn’t work out, it could still be the case that the older workers opt-in to upskilling courses or programs themselves, which would still be a market-based solution to the problem we are currently discussing. 

The hypothesis could be true if the individuals conducted their cost-benefit analysis with complete rationality. Yet as Posthuma and Campion pointed out, older workers tend to trap themselves in the negative stereotype and doubt their capabilities in learning new skills. Such a biased self-impression can easily lead to individuals exaggerating the costs and risks associated with acquiring new skills. Hence, the rational decision-maker hypothesis, which the neoclassical economists rely on, is invalid in the presence of stereotyping. 

The fact that the “invisible hand” in the capital market is not powerful enough to push the labour market to a socially optimal position highlights the importance of policy interventions. 

The EU governments’ past attempt to provide tax subsidies to firms to fund at work training for older employees has led to significant market failures such as over-investment in older worker training programs and excessive transfer of resources from younger workers to older workers. Therefore, it would be in policymaker’s fundamental interest to prevent the deadweight losses and substitution effect caused by a poorly designed instrument. 

A recent study conducted by Vodopivec provides policymakers with a better alternative. That is, direct subsidies through financial vouchers given to older workers conditioning that they are participating in certified training programs tailored to their needs. Such policy reduces the likelihood of spending government funds on inefficient training programs. And in his paper, Vodopivec also proved that vouchers effectively raised the training participation rate in many European countries. 

With all being considered, we should understand the importance and the urgency to upskill the generation who might be left behind in the digital revolution. Yet, policymakers should always have the right instrument in place when handing out support. 

We should let effective programs direct us towards a more efficient economy. 


Charness, N., & Czaja, S. J. (2006). Older worker training: What we know and don’t know.# 2006-22. AARP

Desjardins, R., & Warnke, A. J. (2012). Ageing and skills: A review and analysis of skill gain and skill loss over the lifespan and over time. 

Mnif, S. (2016). Skill biased technological changes: Case of the mena region. Theoretical & Applied Economics, 23 (3). 

Picchio, M. (2021). Is training effective for older workers? IZA World of Labor . Posthuma, R. A., & Campion, M. A. (2009). Age stereotypes in the workplace: Common stereotypes, moderators, and future research directions. Journal of management, 35 (1), 158–188. 

Ristova, C., & Dimitrov, N. (2019). Digitalisation in the hospitality industry-trends that might shape the next stay of guests. International Journal of Information, Business and Management, 11 (3), 144–154. 

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Tihinen, M., K¨a¨ari¨ainen, J., Ailisto, H., Komi, M., Parviainen, P., Tanner, H., . . . others (2016). The industrial internet in finland: on route to success? 

Vodopivec, M., Finn, D., Laporˇsek, S., Vodopivec, M., & Cvornjek, N. (2019). Increasing employment of older workers: Addressing labour market obstacles. Journal of population ageing, 12 (3), 273–298.