Workforce Ageing and Labour Productivity in Europe

Reviewing the Benefits of Aging Populations: Care Activities Provided by the Older People as a Commons

This research reviews the commons paradigm as a framework for understanding the positive contribution of older cohorts to society. The commons, thought as instituting praxis that provide social goods based on autonomy and reciprocity, can help in understanding the role of this age group in providing care to the rest of society. This approach overturns the way economic literature approaches the aging phenomenon. What is understood as a “common evil”—or a problem that needs to be solved—can be analyzed as a “common good.” From this perspective, older people (population aged 65 and over) are essential to European society and the economy to carry out informal care activities that enable and facilitate the “productive” activities of working people.

The Employment Ecosystem of Bizkaia as an Emerging Common in the Face of the Impact of COVID-19

In the context of the impact of COVID-19 pandemic in Bizkaia (Basque Country, Spain), and from the renewed Commons paradigm, this research analyzes the initial response given by the region’s employment ecosystem. Based on extensive quantitative and qualitative methods, it empirically explores the catalytic role that local public and social entities could play in coordinating an organized and systemic response of the employment-related stakeholders to an external impact, such as the current pandemic. The study of databases specifically provided by the Public Administrations for this research, in combination with two survey processes conducted to the main agents of the ecosystem, led to a greater understanding of the benefits of an organized and systemic reaction. From the community identification of a priori unrecognized impacts by individual actors to the proposal of actions closely connected to their short and long-term needs, the article finally presents recommendations aimed at strengthening the resilience and collaboration of the collective action.

Innovation in Company Labor Productivity Management: Data Science Methods Application

The article considers the challenge of labor productivity growth in a company using objective data about economic, demographic and social factors and subjective information about an employees’ health quality. We propose the technology for labor productivity management based on the phased data processing and modeling of quantitative and qualitative data relations, which intended to provide decision making when planning trajectories for labor productivity growth. The technology is supposed to use statistical analysis and machine learning, to support management decision on planning health-saving strategies directed to increase labor productivity. It is proved that to solve the problem of employees’ clustering and design their homogeneous groups, it is properly to use the k-means method, which is more relevant and reliable compared to the clustering method based on Kohonen neural networks. We also test different methods for employees’ classification and predicting of a new employee labor productivity profile and demonstrate that over problem with a lot of qualitative variables, such as gender, education, health self-estimation the support vector machines method has higher accuracy.

Who Is Afraid of Population Aging? Myths, Challenges and an Open Question from the Civil Economy Perspective

Population aging is a great human achievement, but the economic literature normally addresses its effects in a narrow way and as a “problem” to be solved. The objective of this paper is to provide a more balanced approach to aging by calling into question some widespread ideas in the economic literature on aging, such as its supposed negative influence on economic growth, its impact on labor productivity or the assumption that aging societies are incapable of applying reforms. The paper adopts the renewed civil economy framework and takes as a reference the existing literature about beliefs and wrong assumptions on aging. The innovative contribution of this analysis lies in its effort to foster a positive perspective in the population aging field of research and in challenging negative associations regarding old-age stereotypes.

Practical Judgment of Workload Based on Physical Activity, Work Conditions, and Worker's Age in Construction Site

It is important for construction companies to sustain a productive workforce without sacrificing its health and safety. This study aims to develop a practical judgement method to estimate the workload risk of individual construction workers. Based on studies, we developed a workload model comprising a hygrothermal environment, behavioral information, and the physical characteristics of workers). The construction workers’ heart rate and physical activity were measured using the data collected from a wearable device equipped with a biosensor and an acceleration sensor. This study is the first report to use worker physical activity, age, and the wet bulb globe temperature (WBGT) to determine a worker’s physical workload. The accuracy of this health risk judgment result was 89.2%, indicating that it is possible to easily judge the health risk of workers even in an environment where it is difficult to measure the subject in advance. The proposed model and its findings can aid in monitoring the health impacts of working conditions during construction activities, and thereby contribute toward determining workers’ health damage. However, the sampled construction workers are 12 workers, further studies in other working conditions are required to accumulate more evidence and assure the accuracy of the models.

Emotional Status and Productivity: Evidence from the Special Economic Zone in Laos

Employee productivity is a well-studied area, which has been explained in various dimensions. However, there is insufficient research on how workers’ on-job emotional status relates to productivity. This study examined the relationship between workers’ emotional states and productivity by assessing on-job emotionality recorded using a specially designed wearable biometric device. The experiment was conducted at KP Beau Lao Co. Ltd., a Japanese plastic toys and cosmetic products company in Savannakhet province in Southwestern Laos. Participants were 15 plastic toy painters. Mental status, daily output, and other issues were recorded for three consecutive working days. Using random effects panel regression models, we examined how productivity, operationalized as the log of daily output, was related to workers’ emotional states, including the amount of time workers reported being happy, angry, relaxed, and sad. We controlled for conversation time, heart rate, and other demographic features. The results revealed that happiness, and no other emotional state, was significantly and positively related to productivity. Such findings suggested that workers’ emotional states must be addressed as part of an organization’s operational strategy to ensure higher productivity.