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Construction companies are increasingly adopting sensing technologies like laser scanners, making it necessary to upskill the future workforce in this area. However, limited jobsite access hinders experiential learning of laser scanning, necessitating the need for an alternative learning environment. Previously, the authors explored mixed reality (MR) as an alternative learning environment for laser scanning, but to promote seamless learning, such learning environments must be proactive and intelligent. Toward this, the potentials of classification models for detecting user difficulties and learning stages in the MR environment were investigated in this study.

The study adopted machine learning classifiers on eye-tracking data and think-aloud data for detecting learning stages and interaction difficulties during the usability study of laser scanning in the MR environment.

The classification models demonstrated high performance, with neural network classifier showing superior performance (accuracy of 99.9%) during the detection of learning stages and an ensemble showing the highest accuracy of 84.6% for detecting interaction difficulty during laser scanning.

The findings of this study revealed that eye movement data possess significant information about learning stages and interaction difficulties and provide evidence of the potentials of smart MR environments for improved learning experiences in construction education. The research implication further lies in the potential of an intelligent learning environment for providing personalized learning experiences that often culminate in improved learning outcomes. This study further highlights the potential of such an intelligent learning environment in promoting inclusive learning, whereby students with different cognitive capabilities can experience learning tailored to their specific needs irrespective of their individual differences.

The classification models will help detect learners requiring additional support to acquire the necessary technical skills for deploying laser scanners in the construction industry and inform the specific training needs of users to enhance seamless interaction with the learning environment.

Lean and Six Sigma are the two most powerful methodologies for process improvement. They have been widely employed in manufacturing and healthcare industries to achieve substantial cost savings and quality improvement. The purpose of this paper is to investigate the implementation of Lean and Six Sigma for improving logistics operations.

A survey was conducted among 410 companies registered under the Singapore Logistics Association and returned 32 usable responses. χ²-tests were used to identify factors affecting the implementation of Lean and Six Sigma.

It was found that 37.5 per cent of respondents had implemented Lean and the majority of them had implemented Six Sigma together. All implementing companies reported varying degrees of cost savings and productivity improvements. Large logistics companies are more likely to implement Lean and Six Sigma. Companies with a higher service standard are more likely to implement Six Sigma.

The survey was limited to Singapore. Future studies should explore a broader geographical coverage and improve the response rate.

Lean and Six Sigma are applicable for improving logistics operations. Senior management must be committed to support an implementation. Effective training and communications are required for overcoming resistance to change and helping employees to understand improvement methodologies and initiatives.

This research is the very first survey study of Lean and Six Sigma in the logistics industry. It reveals similarities and differences in comparison with the implementation of these methodologies in the manufacturing industry. The findings offer valuable insights for improving logistics operations.

This paper aims to examine common environmental practices and strategies for implementing sustainable FM among Nigerian FM practitioners.

A review of the literature on sustainability and environmental management was undertaken. Data collection was through self‐administered questionnaires directed to a sample of 150 facilities managers who are members of the International Facility Management Association (Nigeria Group), Lagos, Nigeria. Structured interviews with five top facilities management professionals were also conducted. The data collected were analyzed using frequency counts, means, z‐test, repeated measures analysis of variance (ANOVA) and relative importance index. The survey achieved a response rate of 30 percent.

The survey revealed that many of the practitioners put a premium on achieving energy efficiency as a very vital environmental practice within their organizations. A strategic management procedure is more important for the implementation of environmental management in the Nigerian FM industry.

There is a paucity of literature in sustainability within facilities management in Nigeria. An integration of sustainability considerations into FM practice is required to promote the development of suitable environmental initiatives and practices within Nigerian cities, as many facilities managers are employed by companies whose activities harm the environment.