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The health of an economy is heavily dependent on the productivity of the economy's major industries including construction. While most macro-measures of productivity in the USA construction industry indicate a decline, corresponding studies at the individual task level indicate an increase in productivity. Therefore, this paper aims to identify areas where productivity challenges exist and thus provide recommendations for improvement in the construction industry.

A model that relates the way construction projects are executed with the sources of data that inform productivity analyses is developed and presented. This effort/value-flow model informs the data analysis that is performed to determine productivity trends for management and field labor. Further analysis for field labor productivity using field data and management productivity was separately conducted. Management productivity was particularly difficult to gauge, resulting in the use of surrogate measures.

It was observed that while both field labor and management productivities at the industry level have been decreasing, the decrease in management productivity was five times that of field labor productivity. A similar trend was observed for management productivity at the project level.

The primary contribution of this paper to the body of knowledge and industry is the introduction of a holistic analysis of USA construction productivity. Recommendations to improve management productivity include the use of technology, especially project management software.

This paper aims to explore the implications of algorithmic management on careers and employment relationships in the Nigerian gig economy. Specifically, drawing on labour process theory (LPT), this study provides an understanding of the production relations beyond the “traditional standard” to “nonstandard” forms of employment in a gig economy mediated by digital platforms or digital forms of work, especially on ride-hailing platforms (Uber and Bolt).

This study adopted the interpretive qualitative approach and a semi-structured interview of 49 participants, including 46 platform drivers and 3 platform managers from Uber and Bolt.

This study addresses the theoretical underpinnings of the LPT as it relates to algorithmic management and control in the digital platform economy. The study revealed that, despite the ultra-precarious working conditions and persistent uncertainty in employment relations under algorithmic management, the underlying key factors that motivate workers to engage in digital platform work include higher job flexibility and autonomy, as well as having a source of income. This study captured the human-digital interface and labour processes related to digital platform work in Nigeria. Findings of this study also revealed that algorithmic management enables a transactional exchange between platform providers and drivers, while relational exchanges occur between drivers and customers/passengers. Finally, this study highlighted the perceived impact of algorithmic management on the attitude and performance of workers.

The research presents an interesting case study to investigate the influence of algorithmic management and labour processes on employment relationships in the largest emerging economy in Africa.

Studies highlight that poor labour supervision and inadequate labour training facilities are the primary factors that result in labour skill shortages and productivity-related challenges among construction firms. This study aims to assess the construction supervisors’ abilities in providing work-based training elements and evaluating labour skills in construction.

A construction supervisory training programme was newly designed with a set of labour training exercises using comprehensive approaches. A total of 64 construction supervisors were trained to deliver the labour training components for more than 250 labourers working on 23 construction projects in Sri Lanka. The supervisors’ competencies were assessed using a detailed marking guide developed through expert discussions and literature reviews.

The results show the detailed cross-section of a wide range of competencies of the construction supervisors in providing labour training elements with the levels of standards/descriptions. The generalisability of the study applications and the reliability of the results were ensured using statistical tests and expert reviews. The findings further describe the impacts of the well-improved competencies of construction supervisors on labour working patterns and work outputs.

Though the study findings were limited to the Sri Lankan construction sector, the study applications can have a considerable impact on the current/future practices of the construction sector in developing countries as well as other developing industries.

The study outcomes may contribute to a rapid increase in the number of construction supervisors becoming certified assessors of National Vocational Qualifications up to certain levels. This paper describes the further extensive implications and future scopes of the study elaborately.

The study adds new characteristics and values to construction supervision practices that can be remarkable in achieving higher levels of performance and productivity in labour operations. Importantly, the study contributes to adorning the job role of construction supervisors with the title of “labour training expert”.

The role of labor unions in relation to corporate social responsibility (CSR) remains both ambiguous and crucial for union members and business leaders. Given the complex relationship between labor unions and corporations, this study aims to address whether labor unions keep corporations honest (by monitoring CSR activities) or potentially render CSR initiatives less necessary.

Using data from the MSCI Kinder, Lydenberg, Domini Database for firms in the Russell 1000 Index, this study examines the link between labor unions and CSR in U.S. companies over a six year period. Generalized least squares models were used to test the hypotheses for 3,937 firm-year observations.

The findings show that unionized companies generally pay less attention to CSR compared to nonunionized ones. The presence of labor unions and positive union-management relations both show a significant negative impact on CSR ratings, where positive union-management relations negatively affect CSR ratings more than just the presence of labor unions. Further, when considering the environmental, social and governance aspects of CSR separately, the results are more complex, suggesting that the relationship between labor unions and CSR varies depending on specific ESG dimensions.

CSR, a well-researched area, rarely addresses the companies' relationships with labor unions. Studies in South Korea and the UK have touched on the impact of labor unions on CSR, but in the USA it remains unexplored. This study extends this line of work by examining U.S. companies.

This paper aims to examine the impact and mechanism of digital development on enterprise labor productivity. In addition, this study empirically analyzes the nonlinear impact of digitalization on labor productivity.

This paper uses a fixed effect model, a mediation effect model and a panel threshold model to test the theoretical hypothesis of this study.

The results demonstrated that digitalization had a promotional effect on labor productivity, with approximately 18% of this effect achieved through transmission and influence on human capital. In addition, the novelty of this study lies in the discovery that digitization has an obvious nonlinear positive effect on corporate labor productivity. The results suggest that companies should increase investment in data-driven innovation capabilities, improve the implementation of digital talent training plans, improve their financing capacity and strengthen corporate internal management, while the government should provide appropriate policy support differently for various enterprises.

This study takes China’s Shanghai and Shenzhen A-share listed companies as the research object, systematically examines the impact and mechanism of digital development on enterprise labor productivity and explores the nonlinear relationship between digitalization and enterprise labor productivity, which is a new angle.

本文旨在探讨数字化发展对企业劳动生产率的影响及其机制。此外, 本研究实证分析了数字化对劳动生产率的非线性影响。

本文采用固定效应模型、中介效应模型和面板门槛模型来检验本研究的理论假设。

结果表明, 数字化对劳动生产率有促进作用, 其中约 18% 是通过对人力资本的传导和影响来实现的。此外, 本文的新颖之处在于发现了数字化对企业劳动生产率具有显著的非线性正效应。结果表明, 企业应加大对数据驱动创新能力的投入, 完善数字化人才培养计划的实施, 提高融资能力, 加强企业内部管理, 政府应针对各类企业提供差异化的政策支持。

本研究以中国沪深A股上市公司为研究对象, 系统考察了数字化发展对企业劳动生产率的影响和机制, 探讨了数字化与企业劳动生产率之间的非线性关系, 这是一个新的研究角度。

A rise in productivity is associated with higher profits, competitiveness and the sustainability of an industry and a nation. Recent studies highlight inadequate labour supervision and training facilities as the main causes of productivity-related challenges among construction enterprises. This study aims to evaluate the construction supervisors' capabilities in applying the required elements of work practices for enhancing the performance and productivity of construction operations using a case study.

A new construction supervisory training programme was developed through comprehensive sequential processes, and 64 construction supervisors underwent training . Marking guides with different levels of descriptions/standards were developed through consultations with experts and literature reviews, and the supervisors' capabilities were assessed under 64 competency elements of 12 competency units.

The findings show a clear cross-section of all the required competencies of construction supervisors with various levels of standards/descriptions, leading to a new generalised guideline that helps to comprehend what degrees of skills can be taken into account in supervision attributes. Statistical tests and expert reviews were used to ensure the generalisability of the research applications and the reliability of the results.

Despite the study findings being limited to the Sri Lankan construction industry, its applicability could create considerable impacts on the current/future practices of the construction sector in developing countries as well as other developing industries.

The study adds new characteristics and values to construction supervision practices that can be remarkable in encouraging construction supervision to drive the sustainability of construction practices. The study findings are significant in decision-making/planning procedures related to technical comprehension, industry training, scientific documentation, adherence to workforce employment constraints and job outputs. This paper describes the further extensive implications and future scopes of the study elaborately.

This study addresses the knowledge gap in the industry related to the development of protocols and application methodologies necessary to track their performance. The study opens a new window that inflows knowledge attributes to the industry sector along with the necessary comparison of the relevant competency elements to predict/comprehend what levels of capabilities can be theoretically considered and practically applied in supervision characteristics.

Drawing upon a political economy approach, this article aims to analyze the transformations in the labor market within the context of contemporary capitalism, focusing on the phenomenon of financialization.

Financialization is defined as a distinct wealth pattern marked by a growing proportion of financial assets in capitalist wealth. Within financial markets, corporate performance is continuously assessed, in a process that disciplines management to achieve expected financial results, with consequences throughout corporate management.

We find that this phenomenon has implications for labor management, resulting in the intensification of labor processes and the adoption of insecure forms of employment, leading to the fractalization of work. These two mechanisms, added to the indebtedness of workers, constitute three elements for disciplining labor in contemporary capitalism.

We argue that these forms of discipline constitute a subsumption of labor to finance, resulting in an increase in labor exploitation. This formulation of the relationship between financialization and changes in the realm of labor also contributes to understanding the unrealizing potential of social free time in contemporary capitalism.

Regarding human resource and labour relations management, academia focuses mainly on cities; however, rural areas are an integral part of China's economic structure. This study focuses on the movie projection industry in China's rural areas and explores how human resource practices (HRPs) are transformed and the labour process is reconstructed in digital transformation.

We adopt a case study of a rural movie projection company. The company's HRPs reconstructed the labour process of movie projection, and they have been promoted as national standards. Data were collected from in-depth interviews, files and observations.

Rural movie projection companies combine high-performance and paternalistic HRPs in the media industry's digital transformation. HRPs and digital technology jointly reconstruct the labour process. First, the HRPs direct labour process practices towards standardisation. Second, the digital supervision platform guides the control style from simple to technical, placing projectionists under pressure while increasing management efficiency. Third, rural movies made using digital technology have disenchanted rural residents. Accordingly, the conventional relationships between the “country and its citizens,” “individuals themselves,” and “models and individuals” have been removed, and a new relationship between “individuals themselves” is formed thanks to the novel HRPs.

This research plays a crucial role in exposing researchers to the labour process of rural movie projection, which is significant in China but often ignored by Western academia and advances the Chinese contextualisation of research on labour relations.

Existing labor estimation models typically consider only certain construction project types or specific influencing factors. These models are focused on quantifying the total labor hours required, while the utilization rate of the labor during the project is not usually accounted for. This study aims to develop a novel machine learning model to predict the time series of labor resource utilization rate at the work package level.

More than 250 construction work packages collected over a two-year period are used to identify the main contributing factors affecting labor resource requirements. Also, a novel machine learning algorithm – Recurrent Neural Network (RNN) – is adopted to develop a forecasting model that can predict the utilization of labor resources over time.

This paper presents a robust machine learning approach for predicting labor resources’ utilization rates in construction projects based on the identified contributing factors. The machine learning approach is found to result in a reliable time series forecasting model that uses the RNN algorithm. The proposed model indicates the capability of machine learning algorithms in facilitating the traditional challenges in construction industry.

The findings point to the suitability of state-of-the-art machine learning techniques for developing predictive models to forecast the utilization rate of labor resources in construction projects, as well as for supporting project managers by providing forecasting tool for labor estimations at the work package level before detailed activity schedules have been generated. Accordingly, the proposed approach facilitates resource allocation and enables prioritization of available resources to enhance the overall performance of projects.

Working conditions, pay rates and the rights of workers to collectively negotiate have become important points of discussions in recent years, with support for unions and union applications rising to levels long unseen in America. In many instances, though, companies have responded aggressively. This is not the first time such a dynamic has played out in American business. This study aims to take a fresh look at one of America’s most prominent historical disputes between labor and ownership – the Homestead Massacre of 1892 – to glean lessons from that conflict that remain relevant to today’s business environment.

This study adopts game theory and the principles of repeated interaction to assess how differing discount factors led to differences in time orientations between the workers and the Carnegie company. These differing time orientations affected both the strategy each side deployed in the negotiations and the payoffs received by the parties. Letters, contemporary news reports and histories of the events leading up to and immediately following the 1892 Homestead Massacre are qualitatively analyzed with a genealogical pragmatic approach.

Differences in temporal orientation between management and workers exacerbated the conflict, with the workers adopting a more cooperative stance and distal time orientation, while the Carnegie company negotiated with a proximal time orientation and played to “win” a game that, in fact, could not be fully won or lost given its infinitely repeating nature. The result was a short-term victory for the Carnegie company but with long-term negative consequences that highlight the suboptimal outcome the company achieved by playing a proximal strategy in an infinite game.

Although the incident at Homestead is a well-studied labor dispute, many of the themes that preceded the incident have resurfaced in the modern work context. This work, by adopting game theory as an analytical framework, provides new insights into management mistakes that led to the labor conflict and lessons for what present-day managers can do to avoid exacerbating labor strife.