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A contrast of site productivity levels for an in situ concrete operation (reinforcement fixing) on a high‐rise project amongst construction contractors from Germany, France and the UK is given. The productivity rates provided by contractors' planning engineers for a model construction project form the basis of this evaluation. Conclusions drawn, based on relatively small samples, are considered approximations of the actual productivity levels in each international location. An analysis of variance based on international origin indicates significant differences between these productivity rates. Generally, amongst the sample surveyed, UK and German contractors exhibit the most efficient levels of labour productivity for the operations observed, whilst French contractors are by far the least productive. For the model building, UK contractors are the most productive, requiring less labour input than those from Germany and France. The UK contractors also demonstrate a high degree of performance variation. Leading on from these analyses, a construction (labour) cost comparison indicates the UK to be the most economic location. A comparison with previous research indicates contrasting findings. It is concluded that the performance ranking of French, German and UK contractors will vary depending upon the construction operations concerned, and therefore, assumptions regarding national contracting industries should not be based on individual operations. Contractors could benefit from developing closer links with their international counterparts since this would facilitate dissemination of European ‘best practice’.

This research seeks to evaluate the impact of applying lean construction principles on the performance of reinforcement operations using a discrete-event simulation (DES) approach.

Process mapping of reinforcements operations was first established through field observation and interviews with construction managers involved in the selected project. Subsequently, quantitative data were gathered and then used to identify the best probabilistic density functions for each activity duration based on the fit-quality tests. Upon testing the validity of the real-world model, a lean simulation model was developed, using ARENA software, to investigate the impact of lean construction principles on the performance of such processes.

Lean principles are effective in enhancing the performance of the selected construction process. Output performance measurements for real-world model and lean model revealed that lean construction principles led to 41% improvement in process productivity, 14% enhancement in process efficiency and 17% reduction in cycle time.

The statistical findings only represent the process under study (reinforcement process) and cannot be generalized to other construction activities. In order to draw generalizable conclusions, future works are needed to extend this study to different project sizes and more complex construction processes (e.g. bricklaying process and concrete pouring operations). Moreover, there are other factors such as labor skills, rework and uncertainty, site conditions that require further analyses for leaner construction projects.

The methodology and the techniques presented in this work can be used for decision making by analyzing various lean construction scenarios and evaluating their impacts on performance outcomes of any construction process prior to real-world implementation.

The present paper reports on the development of SITE EXPERT: a prototype knowledge‐based expert system. It is an advisory system. SITE EXPERT is intended to be used for productivity improvement in construction and provides advice on: (1) the productivity of three basic operations of construction, i.e. pouring and placing of concrete, erection and removal of formwork, and fixing reinforcement; and (2) human resources and site layout as productivity factors. The system uses information from construction experts, text books, data recorded at construction sites and the engineer's own knowledge, as well as knowledge obtained by running simulation models. In the present paper, the development, operation and evaluation of the prototype system is described. The results of this prototype system development demonstrate that artificial intelligence methodologies provide powerful facilities for capturing information about construction processes and advising the practitioners of construction on productivity improvement within a computer format close to human reasoning.

The purpose of this paper is to show how the time frame for the execution of a construction project in Algeria is rarely respected because of organizational problems and uncertainties encountered while the execution is underway.

A case study on the construction of a metro station is used as a pilot project to show the effectiveness of replacing traditional construction processes by more innovative procedures. Concurrent engineering (CE) is applied to optimize the execution time of the underground structure. A numerical simulation is integrated into the construction process in order to update design parameters with real site conditions observed during the construction process.

The results show that the implementation of CE is efficient in reducing the completion time, with an 18 per cent reduction observed in this case study. A cost reduction of 20 per cent on the steel frame support and a total cost reduction of 3 per cent were obtained.

The study demonstrates that the application of CE methods can be quite valuable in large, complex construction projects. Vulgarizing it as “the solution” to adjust time frame delay, control quality and cost, might be an issue for local construction enterprises in Algeria.

Using the concept of CE by overlapping different activities involved in a construction project and making use of simulation tools in the process at different stages of the execution have resulted in modifying the excavation method and hence reducing the completion times.

This study aims to examine how expatriates’ knowledge can be adopted to transform the mental models at the subsidiary level and develop a sustainability-driven learning organization in the context of emerging multinational enterprises (EMNEs).

Through an inductive interpretive analysis of three Haier subsidiaries from developing countries, this study compares between old and new understandings of sustainability and examines how expatriates’ knowledge can facilitate shifts toward the new to foster a sustainability-driven learning organization.

The authors find that subsidiary employees face strategic and operational ambiguity concerning sustainability issues and that a mix of dissemination and reinforcement routines that align with headquarters’ expectations are used to maintain a continuous sustainability-driven learning pattern. Though EMNE subsidiaries may have contrasting understandings of sustainability, expatriate knowledge transfer can help change subsidiaries’ mental models and thus create sustainable capabilities and mindsets that form a sustainability-driven learning organization at the subsidiary level.

This study reveals the potential in applying expatriate knowledge transfer to transforming sustainable mental models in building sustainability-driven learning organizations.

This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations.

A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy.

The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems.

This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

This paper aims to discuss the suitability of topic modeling as a review method, identifies and compares the machine learning (ML) research trends in five primary business organization verticals.

This study presents a review framework of published research about adopting ML techniques in a business organization context. It identifies research trends and issues using topic modeling through the Latent Dirichlet allocation technique in conjunction with other text analysis techniques in five primary business verticals – human resources (HR), marketing, operations, strategy and finance.

The results identify that the ML adoption is maximum in the marketing domain and minimum in the HR domain. The operations domain witnesses the application of ML to the maximum number of distinct research areas. The results also help to identify the potential areas of ML applications in future.

This paper contributes to the existing literature by finding trends of ML applications in the business domain through the review of published research. Although there is a growth of research publications in ML in the business domain, literature review papers are scarce. Therefore, the endeavor of this study is to do a thorough review of the current status of ML applications in business by analyzing research articles published in the past ten years in various journals.

The unique nature of the construction sector makes it fall behind other sectors in terms of productivity. Monitoring construction productivity is crucial for the construction project's success. Current practices for construction productivity monitoring are time-consuming, manned and error prone. Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity.

This study aims to investigate and assess the different techniques used for monitoring productivity in building construction projects. Therefore, a mixed review methodology (bibliometric analysis and systematic review) was adopted. All the related publications were collected from different databases, which were further screened to get the most relevant based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria.

A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. Also, it was observed that current studies did not cover all the complex construction job sites and they were applied based on a small sample of construction workers and machines separately.

This review paper contributes to the literature on construction management by providing insight into different productivity monitoring techniques.

Building on the routine dynamics literature, this paper aims to expand our philosophical, practical and infrastructural understanding of implementing lean production. The authors provide a process view on the interplay between lean operating routines and continuous improvement (CI) routines and the roles of different actors in initiating and establishing these routines.

Using data from interviews, observations and document analysis, retrospective comparative analyses of three embedded case studies on lean implementations provide a process understanding of enacting and patterning lean operating and CI routines in manufacturing SMEs.

Incorporating the “who” and “how” next to the “what” of practices and routines helps explain that rather than being implemented in isolation or even in conjunction with each other, sustainable lean practices and routines come about through team leader and employee enactment of the CI practices and routines. Neglecting these patterns aligned with unsustainable implementations.

The proposed process model provides a valuable way to integrate variance and process streams of literature to better understand lean production implementations.

The process model helps manufacturing managers, policy makers, consultants and educators to reconsider their approach to implementing lean production or teaching how to do so.

Nuancing the existing lean implementation literature, the proposed process model shows that CI routines do not stem from implementing lean operating routines. Rather, the model highlights the importance of active engagement of actors at multiple organizational levels and strong connections between and across levels to change routines and work practices for implementing lean production.

The miners' strike of 1984–5 does not lend itself easily to general conclusions. It was, and it is hoped will remain, unique. Nevertheless, it laid bare some significant trends and developments in the policing of industrial disputes, which have, in several respects, been reinforced by subsequent events. My purpose in this article is to identify and analyse what happened in the policing of the strike in that context, in an attempt to highlight the implications of contemporary techniques of policing disputes and of the context in which policing takes place. My central thesis is that recent developments in policing disputes are potentially dangerous for civil liberties, for the police themselves and for industrial relations.