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The purpose of this paper is to test the impact of selected characteristics of jobseekers on employers’ decisions regarding potential hires (direct and probabilistic signals). The main focus of the study is to test the impact of jobseekers’ participation in selected active labour market programmes on employers’ hiring decisions for three positions: unskilled worker, skilled worker and administrative employee. Other characteristics tested include age, gender, presence of children in the household, state of health, experience of short- and long-term unemployment and indebtedness.

This study analyses data from a representative survey of employers with five or more employees in the Czech Republic. The survey was conducted in December 2020 using stratified random sampling, combining online questionnaires and personal interviews. The study includes 1,040 employers and uses the factorial survey experiment (FSE) design.

The results of the FSE suggest that the perceived positive impact of completing one of the activation programmes depends on the position for which the candidate is being recruited. While for the unskilled job category, the completion of any of the tested schemes (training, subsidised jobs or public works) had a positive effect; for the skilled job category, only the training and subsidised jobs schemes had a positive effect; and for the administrative job category, public works programme even had a negative effect.

A somewhat limiting factor in the context of this study seems to be the definitions of the positions tested (unskilled and skilled workers and administrative staff). The decision-making of the respondents was somewhat restricted by such broadly defined categories. Typically, studies with FSE designs have a focus on a specific sector of the economy, which allows for a better definition of the positions or jobs under test. The relationship between position and the impact of individual characteristics is clearly a matter for further research.

The results of the study confirm that completion of the activation programme, as well as other candidate characteristics, constitute differentiating signals for employers that influence their hiring decisions. At the same time, there is evidence that the training programme and the subsidised jobs programme are effective in terms of increasing participants’ chances of employment.

The demand side should be included in the evaluation of activation policies. The design of the FSE provides an appropriate way to test the impact of activation measures on the decision-making of employers.

The farm sector is crucial for rural poverty alleviation, alongside the non-farm sector, which contributes to mitigating risks associated with crop failures. This paper investigates the effects of public policies on productive employment within both the farm and non-farm sectors in sub-Saharan Africa.

A meta-analysis is conducted exclusively on the results of the Partnership for Economic Policy (PEP)-funded studies under the Policy Analysis on Growth and Employment (PAGE II) initiative. Selected studies focused on the impact of public policies on productive employment in rural farm and non-farm sectors, encompassing a total of nine sub-Saharan Africa countries in: Benin, Burkina Faso, Cote d'Ivoire, Democratic Republic of Congo, Ghana, Lesotho, Nigeria, Senegal and South Africa.

The results indicate that public investments in rural areas and public policies that facilitate access to productive resources are likely to enhance productive employment. The overall effect size is positive and significant, ranging from 2% to 10% increases in productive employment. Sources of variation include the sector of activity and the policy instrument. In addition, the policy effects are gender-sensitive and seem more consistent in the non-farm sector.

Although the selected working papers addressed several aspects of productive employment, other aspects warrant further investigation. Policies involving restrictions or regulations have received little attention in the impact analysis. Researches to fill this gap would be important. Another suggestion for further research is the analysis of the relative importance of non-farm employment in rural areas in developing countries. It is always assumed that rural households depend heavily on agriculture for their subsistence.

The contribution of the paper lies in the comparative analysis of numerous public policies implemented in nine distinct countries. By consolidating data from fourteen 14 different experiences into a single study, the paper offers valuable insights on factors that determine policy effectiveness and contribute to understanding what worked for whom and why.

The purpose of this paper is twofold: first, a case study on applying lean principles in manufacturing operations to redesign and optimize an electronic device assembly process and its impact on performance and second, introducing cardboard prototyping as a Kaizen tool offering a novel approach to testing and simulating improvement scenarios.

The study employs value stream mapping, root cause analysis, and brainstorming tools to identify root causes of poor performance, followed by deploying a Kaizen event to redesign and optimize an electronic device assembly process. Using physical models, bottlenecks and opportunities for improvement were identified by the Kaizen approach at the workstations and assembly lines, enabling the testing of various scenarios and ideas. Changes in lead times, throughput, work in process inventory and assembly performance were analyzed and documented.

Pre- and post-improvement measures are provided to demonstrate the impact of the Kaizen event on the performance of the assembly cell. The study reveals that implementing lean tools and techniques reduced costs and increased throughput by reducing assembly cycle times, manufacturing lead time, space utilization, labor overtime and work-in-process inventory requirements.

This paper adds a new dimension to applying the Kaizen methodology in manufacturing processes by introducing cardboard prototyping, which offers a novel way of testing and simulating different scenarios for improvement. The paper describes the process implementation in detail, including the techniques and data utilized to improve the process.

Inflation and federal monetary efforts to control it with interest rate hikes have very real and overwhelmingly negative consequences on US local governments following the onset of COVID-19. This study explores the post-pandemic inflationary environment of US local governments; examines the impacts of inflation and high interest rates on local government revenue, operating costs, capital costs, and debt service; reviews local government inflation management strategies, including the use of intergovernmental revenue; and assesses ongoing threats to local government financial health and financial resilience.

This study uses trend and literature analysis to comment on current issues local governments face.

The study finds that the growth of property values and resulting stability of property tax revenue has been important to local government revenues; that local governments bear very real burdens as operating and capital costs increase; and that the combination of high inflation and interest rates affects local government debt issuance by negatively affecting credit quality and interest costs, leading to municipal market contraction. Local governments have benefitted tremendously from intergovernmental revenue, but would be ill-advised to rely on it.

Vulnerabilities owing from revenue mismatch with the economy; inadequate affordable housing, inequality, and social issues; a changing workforce and tight labor market; climate change; and federal fiscal contraction—all of which are exacerbated by high inflation and interest rates—require local governments to act strategically, boldly and collaboratively to achieve fiscal health and financial resilience, and to realize positive returns of investments in people and capital.

This work is unique in addressing the post-pandemic impact of inflation and interest rates on local governments.

After the decision of the Egyptian government to adhere to the Equal Pay International Coalition in 2020, a great deal needs to be done to guarantee ‘equal pay for equal work’. The authors provide a comprehensive, in-depth, up-to-date analysis of the gender wage gap in Egypt, as well as its evolution over the last 20 years, disaggregated by public and private sector. The authors also provide an analysis of the cultural determinants of Egypt's low female participation.

The authors apply the Oaxaca-Blinder decomposition (with sample selection) to assess the gender wage gap at the mean of the wage distribution in the public and private sector. The authors also implement a re-centred influence function decomposition to assess the extent of ‘discrimination’ along the wage distribution in both sectors. An inverse-probability-weighted regression adjustment procedure is used to assess the joint impact of gender and firm-ownership. A female participation equation taking into account gender equality attitude is provided.

The authors find a sizable and increasing gender wage gap in the private sector almost entirely due to ‘discrimination’. The authors also find evidence of a sticky floor in the private sector and a glass ceiling in the public one. Cultural barriers play a major role in determining female participation.

This is the first paper on the evolution of gender equality in Egypt that takes into account the effect of the 'Arab Spring’ of 2011. To the best of the authors’ knowledge, this is also the first time that an IPWRA procedure is applied to study the interaction effect of gender and firm-ownership.

With hybrid simulation techniques getting popular for systems improvement in multiple fields, this study aims to provide insight on the use of hybrid simulation to assess the effect of lean manufacturing (LM) techniques on manufacturing facilities and the transition of a mass production (MP) facility to incorporating LM techniques.

In this paper, the authors apply a hybrid simulation approach to improve an educational automotive assembly line and provide guidelines for implementing different LM techniques. Specifically, the authors describe the design, development, verification and validation of a hybrid discrete-event and agent-based simulation model of a LEGO® car assembly line to analyze, improve and assess the system’s performance. The simulation approach examines the base model (MP) and an alternative scenario (just-in-time [JIT] with Heijunka).

The hybrid simulation approach effectively models the facility. The alternative simulation scenario (implementing JIT and Heijunka LM techniques) improved all examined performance metrics. In more detail, the system’s lead time was reduced by 47.37%, the throughput increased by 5.99% and the work-in-progress for workstations decreased by up to 56.73%.

This novel hybrid simulation approach provides insight and can be potentially extrapolated to model other manufacturing facilities and evaluate transition scenarios from MP to LM.

The popular uprising in Sri Lanka on July 9th, 2022, led to President Gotabaya Rajapaksa fleeing the country. It represented a stunning culmination of a wave of protests during the recent past. The proximate cause of the uprising was the worst economic crisis that Sri Lanka had experienced since the Great Depression of the 1930s. The breakdown was long in the making since the island nation became the first country in South Asia to take the neoliberal turn in the late 1970s. The dramatic collapse was catalyzed by a sovereign debt crisis with the onset of the COVID-19 pandemic and the war in Ukraine. Nevertheless, like all great revolts, it has led to a counter revolution by the ruling class, including the reconfiguration of the old regime.

We examine the tremendous consequences of recent events, both in terms of Sri Lanka's long history of struggles involving working people and the global unravelling underway. We explore whether Sri Lanka is a harbinger of more global political economic changes to come. The process includes the possibility of systemic resistance to financialization in the scores of countries in the Global South experiencing tremendous debt distress. In this regard, we ask whether Sri Lanka's revolt could yet become a revolution. To frame the potential implications, we turn to a deeper interrogation of classic Marxist theories and concepts.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

In this study, workplace spirituality is discussed in the context of remote work and the COVID-19 pandemic. First, the focus is on the changes in the meaning and function of employees in the organization during the evolutionary process of industrialization and management paradigms. Afterward, conceptual frameworks for spirituality and workplace spirituality are presented, and in the last section, academic studies that deal with workplace spirituality with distance or hybrid work arrangements are included. Early studies offer insights and recommendations on conceptualizing, developing, and managing workplace spirituality. They all emphasize that spirituality is necessary for remote work as a tool to overcome stress and mental health problems and increase employee well-being. Unfortunately, the remote work and workplace spirituality literature is relatively narrow and needs to be expanded.