Improvement of Resource Utilisation Through Forecasting, Planning, and Information Flow

Demand forecasting and production planning are challenging issues when working to supply perishable goods to fulfil supermarket requirements as opposed to dry goods that can be manufactured and have a fixed storage life. The focus of this report is on the improvement of resource utilisation through better forecasting, planning, and information flow. There is a fluctuation for labour demand within the processing function; controlling the number of staff daily is vital to the efficient running of production and waste reduction. It is the belief for the management that left unchecked the production planners can tend to overorder staff as a contingency.

London at work

This chapter offers a detailed consideration of London’s labour market, exploring the high degree of seasonality that applied in a reconstruction of London’s Roman working year. The harbour relied on inputs of manual labour and ox-drawn haulage, serving the needs of dozens of vessels docked against the quays or beached on the river foreshore. Demand was intensive during the summer sailing season, but negligible in the winter. London’s construction industry was similarly labour-intensive and seasonal. These demands combined to present high levels of labour demand from spring to autumn, interrupted by slack winters of underemployment. Some needs may have been met by seasonal immigration from the countryside, but a lack of evidence for knowledge exchange between town and country suggests that this was not on a large scale. It is more likely that labour, perhaps including a relatively high proportion of slaves, was redirected into industry and craft production as stock was built up against spring needs. The chapter reviews the evidence for these shops and workshops, and for industrial production in and around Roman London. Particular emphasis is given to the importance of shipbuilding, and the demand this placed on supplies of timber and iron. Other industries to receive attention include potting, tanning and leatherworking, and glassmaking.

Monopsony power and the demand for low-skilled workers

This study analyses firms’ labour demand when employers have at least some monopsony power. It is argued that without taking into account (quasi-)monopsonistic structures of the labour market, wrong predictions are made about the effects of minimum wages. Using switching fractional panel probit regressions with German establishment data, I find that slightly more than 80% of establishments exercise some degree of monopsony power in their demand for low-skilled workers. The outcome suggests that a 1% increase in payments for low-skilled workers would, in these firms, increase employment for this group by 1.12%, while firms without monopsony power reduce the number of low-skilled, by about 1.63% for the same increase in remuneration. The study can probably also be used to explain the limited employment effects of the introduction of a statutory minimum wage in Germany and thus leads to a better understanding of the labour market for low-skilled workers. JEL Codes: J23, J42, C23, D24

Essential Farmworkers and the Pandemic Crisis: Migrant Labour Conditions, and Legal and Political Responses in Italy and Spain

The agri-food system across Europe relies heavily on migrant labour. Border lockdowns during the Covid-19 pandemic immobilised thousands of foreign farmworkers, giving rise to fears of labour shortages and food production losses in EU countries. Farmers’ organisations sought institutional interventions to address this labour demand. Although migrant workers have become a fundamental component of core sectors in recent decades, it is only in the current health emergency that they were recognised as ‘essential’ workers. The chapter analyses the working conditions of migrant farmworkers alongside national debates and institutional interventions in Italy and Spain during the pandemic. It provides a critical comparative analysis of legal and policy interventions to address migrants’ situations of vulnerability. Both countries depend on important contingents of EU and non-EU migrant farmworkers, especially in fruit and vegetable production; moreover, they present common aspects in supply chain dynamics and labour market policies, but also specific differences in labour, migration and social policies. Both adopted measures to face the condition of irregularity of migrant workers in order to respond to labour demand in the agri-food sector and to provide these workers with safe working and living conditions during the pandemic. However, these interventions reveal shortcomings that significantly limit their impact and outcomes, calling into question to what extent migrant workers are really considered as ‘essential’ in a long-term perspective and, therefore, to what extent the current pandemic constitutes an opportunity for a new push to enforce labour and migrant rights.

Better understanding of the labour market using Big Data

Motivation: As the result of digitalisation of the economy, the number of Internet users is increasing, which leads to an increase in the number of vacancies posted on online platforms and services. The description of vacancies includes information about skills and competencies, which is the source of additional data for the labour market analysis. This information cannot be received through the analysis of statistical and administrative data. Therefore, it is important: — to learn how to evaluate new information sources, and use the data they generate; — to develop tools that people and organizations will use for finding an employee or a vacant post. The study focuses on the analysis and forecast of labour demand in the context of skills and competencies, which significantly enriches and adds to the information about the labour market and facilitates effective decision-making. Aim: The main goals of this article are the following: (1) identification of the methodological approaches in the labour market analyses using Big Data; (2) assessment of the labour demand and labour supply in the context of skills and competencies listed in the vacancy description posted on job portals; and (3) determination of the matches (mismatches) between skills and competencies in order to help the companies and individuals get better employment and education. Empirical data used in the research were collected from the description of job vacancies (16 401 vacancies) and CVs (227 215 CVs) from the most popular open job portals in Belarus through the scraping approach and classified according to the ESCO and ISCO codes. Quantitative analysis by the means of artificial intelligence was used in the research. Results: The study results revealed that the information about the volume and structure of skills and competencies obtained by scraping data from vacancy descriptions and Cvs, which are posted on online portals, allows for more precise diagnostics of labour demand and supply and overcoming of bilateral information asymmetry in the labour market. Based on the analysis, the parameters of scarcity and excess in competencies for individual occupations in the labour market are determined (the level of the correlation ratio between applicants’ competencies and those requested by employers in the context of occupations (four digits according to the ISCO classification) is less 0.8; the deviation of the ranks of competencies listed in CVs and vacancy descriptions according to the ESCO groups of skills/competencies and a sign of revealed deviations). The methodology is developed to set areas for necessary knowledge acquisition (by the analysis of competencies listed in CVs and vacancy descriptions at the 3rd and 4th digit level of ISCED classification) and skills (by the analysis of competencies at the 2nd digit level in ESCO groups). The paper illustrates limitations in using Big Data as an empirical database and explains the measures to eliminate those limitations.

Determinants of Unemployment in the Large and Medium Industrial Sector in Indonesia

As a country with the second-highest unemployment rate, Indonesian policymakers should worry about this condition. Based on the macroeconomic perspective, unemployment is affected by the firms' labour demand. It highlights that the firm's profit or loss highly determines the labour force demand. Using the Fixed Effect Model, this study results show that the labour force significantly affects industrial output, and the changes of industrial output highly increase the labour demand in the market. However, foreign and domestic capital neither significantly reduce unemployment rate in Indonesia nor stimulate the large and medium industries to absorb labour in the market. The Government should utilize foreign and domestic capital efficiently as possible to reduce unemployment rate.

Assessment of the Effect of Technological Innovations on Unemployment in the European Union Countries

Innovation and unemployment are two economic elements related to each other that have been constantly analyzed in the economic debates from the beginning of the 21st century. A classical question is whether innovation creates or destroys jobs. The conventional approach contemplates innovation as a transformation instrument of an economy, resulting in economic growth and jobs creation. Another approach points out to various mechanisms which can compensate the primary effect of innovations and cause an ultimate effect of innovations on labour demand to be unclear. In view of the fact that there are many different explanations about the impact of innovations on labour demand, this paper, after the analysis of theoretical and empirical scientific literature in this field, provides an empirical analysis with unemployment as the dependent variable. The authors use data from 28 European Union countries for the period of 1992–2016 and pursue to research how technological innovations affect unemployment rate. There are two core independent variables – expenditure on R&D (research and development) and number of patent applications – as the main proxies for technological innovations. Control variables that affect unemployment are included to the model as well. The model was estimated using a dynamic two-step System Generalized Method of Moments (GMM-SYS) of a panel data system. After the composition of 12 different estimations of the model, the results suggest that, in some cases, technological innovations affect unemployment.

Introduction

Structural change is an important dimension of socio-economic development, closely connected with economic growth, as well as with innovation and technological change, international trade, political economy, employment dynamics and labour demand, inequality and poverty, and climate change, among many others. The current volume discusses the relationships between these and other factors and structural change, with this introductory chapter providing an analytic overview of the major themes discussed in the volume. The chapter seeks to discuss these issues in broad terms, highlighting the complex interactions between structural change and these different factors, thereby emphasizing the myriad ways through which structural change can impact upon—and be affected by—socio-economic outcomes.