Mahesh Babu Purushothaman and Jeff Seadon
This review paper, using a systematic literature review (SLR) approach, aims to unravel the various system-wide waste in the construction industry and highlight the connectivity…
Abstract
Purpose
This review paper, using a systematic literature review (SLR) approach, aims to unravel the various system-wide waste in the construction industry and highlight the connectivity to construction phases, namely men, materials, machines, methods and measurement (5M) and impacting factors.
Design/methodology/approach
This study used an SLR approach and examined articles published since the 2000s to explore the connectivity of system-wide waste to construction phases, 5M and impacting factors. The results are given in table forms and a causal loop diagram.
Findings
Results show that the construction and demolition (CD) waste research carried out from various perspectives is standalone. The review identified ten types of system-wide waste with strong interlinks in the construction industry. The finding highlights connectivity between wastes other than material, labour and time and the wastes' impacting factors. Further, the review results highlighted the solid connectivity for construction phases, 5M, and impacting factors such as productivity (P), delay (D), accidents (A), resource utilisation (R) and cost(C).
Research limitations/implications
SLR methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, fruitful articles hiding in less popular journals may not be included in the well-known database that was searched. Researcher bias of the authors and other researchers that authored the articles referred to is a limitation. These limitations are acknowledged.
Practical implications
This article unravels the construction system-wide waste and the waste's interlinks, which would aid industry understanding and focus on eliminating the waste. The article highlights the connectivity of system-wide wastes to 5M, which would help better understand the causes of the waste. Further, the paper discusses the connectivity of system-wide waste, 5M and P, D, A, R and C that would aid the organisation's overall performance. The practical and theoretical implications include a better understanding of waste types to help capture better data for waste reduction and productivity improvement. The operating managers could use the tracking of wastes to compare estimated and actual resources at every process stage. This article on system-wide waste, 5M and P, D, A, R and C, relationships and their effects can theorize that the construction industry is more likely to identify clear root causes of waste now than previously. The theoretical implications include enhanced understanding for academics on connectivity between waste, 5M and P, D, A, R and C that the academics can use and expand to provide new insights to existing knowledge.
Originality/value
For the first time, this article categorised and highlighted the ten types of waste in construction industries and the industries' connectivity to construction phases, 5M and impacting factors.
Details
Keywords
Purushothaman Mahesh Babu, Jeff Seadon and Dave Moore
The purpose of this paper is to highlight the prominent cognitive biases that influence Lean practices in organisations that have a multi-cultural work environment which will aid…
Abstract
Purpose
The purpose of this paper is to highlight the prominent cognitive biases that influence Lean practices in organisations that have a multi-cultural work environment which will aid the organisational managers and academics in enhancing the understanding of the human thought process and mitigate them suitably.
Design/methodology/approach
A multiple case study was conducted in organisations that were previously committed to Lean practices and had a multi-cultural work environment. This research was conducted on five companies based on 99 in-depth semi-structured interviews and seven process observations that sought to establish the system-wide cognitive biases present in a multi-cultural Lean environment.
Findings
The novel findings indicate that nine new biases influence Lean implementation and practices in a multi-cultural environment. This study also found strong connectivity between Lean practices and 45 previously identified biases that could affect positively or negatively the lean methodologies and their implementation. Biases were resilient enough that their influence on Lean in multi-cultural workplaces, even with transient populations, did not demonstrate cultural differentiation.
Research limitations/implications
Like any qualitative research, constructivism and narrative analyses are subjected to understanding based on knowledge gained on the subject, and data may have been interpreted differently. Constructivist co-recreation of process scenarios based result limitations is therefore acknowledged. The interactive participation in exploring the knowledge sought after and interaction that could have a probable influence on the participant need to be acknowledged. However, the research design, multiple methods of data collection, generalisation based on data collection and analysis methods limit the effects of these and findings are reliable to a greater extent.
Practical implications
The results can provide an enhanced understanding of biases and insights into a new managerial approach to take remedial steps on biases’ influence on Lean practices that can result in improved productivity and well-being from a business process perspective. Understanding and mitigating the prominent biases can aid Lean manufacturing processes and support decision makers and line managers in improving lean methodologies’ effectiveness and productivity. The biases can be negated and used to implement decisions with ease. The influence of biases and the model could be used as a basis to counter implementation barriers.
Originality/value
To the best of the authors’ knowledge, this is the first study that connects the cognitive perspectives of Lean business processes in a multi-cultural environment to identify the cognitive biases that influence Lean practices in organisations that were previously committed to Lean practices. The novel findings indicate that nine new biases and 45 previously identified biases influence Lean implementation and practices in a multi-cultural environment. The second novelty of this study shows the connection between cognitive biases, Lean implementation and practices in multi-cultural business processes.
Details
Keywords
Fei Ying, John Tookey and Jeff Seadon
Construction logistics is an essential part of Construction Supply Chain Management for both project management and cost aspects. The quantum of money that is embodied in the…
Abstract
Purpose
Construction logistics is an essential part of Construction Supply Chain Management for both project management and cost aspects. The quantum of money that is embodied in the transportation of materials to site could be 39–58 per cent of total logistics costs and between 4 and 10 per cent of the product selling price for many firms. However, limited attention has been paid to measure the logistics performance at the operational level in the construction industry. The purpose of this paper is to contribute to the knowledge about managing logistics costs by setting a key performance indicator (KPI) based on the number of vehicle movements to the construction site.
Design/methodology/approach
A case study approach was adopted with on-site observations and interviews. Observations were performed from the start of construction until “hand-over” to the building owner. A selection of construction suppliers and subcontractors involved in the studied project were interviewed.
Findings
Data analysis of vehicle movements suggested that construction transportation costs can be monitored and managed. The identified number of vehicle movements as a KPI offers a significant step towards logistics performance management in construction projects.
Originality/value
This research paper demonstrates that framework of using vehicular movements meet the criterion of effective KPI and is able to detect rooms for improvements. The key findings shed valuable insight for industry practitioners in initiating the measurement and monitor “the invisible logistics costs and performance”. It provides a basis for benchmarking that enables comparison, learning and improvement and thereby continuous enhancement of best practice at the operational level, which may accelerate the slow SCM implementation in the construction industry.
Details
Keywords
Jeff Seadon and John E. Tookey
The New Zealand construction sector is similar to many other countries with a few large companies and many small and micro enterprises. It seeks to achieve a 20 per cent increase…
Abstract
Purpose
The New Zealand construction sector is similar to many other countries with a few large companies and many small and micro enterprises. It seeks to achieve a 20 per cent increase in productivity by 2020 which requires a step change in how the sector operates and buy-in from key stakeholders. The purpose of this paper is to provide a set of levers to improve productivity in the construction sector and develop an implementation schedule.
Design/methodology/approach
This paper adopts a systems approach taking account of the nature of the building sector and the whole life cycle of a building from design to end-of-life. Information gained from the post-construction phases informs the pre-construction and construction phases.
Findings
Productivity is an integrated model whereby increases in process efficiency are executed with quality materials and workmanship, in a manner that is affordable for both the client and contractor and sustainable over time. A series of interviews and workshops produced 10 nodal points and 19 crucial levers which were prioritised for implementation. Additionally, indicators were developed to monitor progress over time and provide information for further corrective action to the system.
Practical implications
The effect of using a few targeted levers in unison provided significantly more gains than individual applications. Modelling real world responses to process stimuli outlined in this paper is extremely valuable. This provided the opportunity for key construction stakeholders to estimate the effects of decision making during a project.
Originality/value
Previous studies identified factors affecting productivity. Piecemeal approaches to improve productivity have resulted in systemic failure. A whole of life approach provides valuable insights to improve productivity in the construction and pre-construction phases which have a flow-on effect through the life cycle. Importantly, this research proposes drivers, an implementation scheme and indicators that provide leverage on nodal points to improve productivity.
Details
Keywords
Mahesh Babu Purushothaman, Jeff Seadon and Dave Moore
This study aims to highlight the system-wide potential relationships between forms of human bias, selected Lean tools and types of waste in a manufacturing process.
Abstract
Purpose
This study aims to highlight the system-wide potential relationships between forms of human bias, selected Lean tools and types of waste in a manufacturing process.
Design/methodology/approach
A longitudinal single-site ethnographic case study using digital processing to make a material receiving process Lean was adopted. An inherent knowledge process with internal stakeholders in a stimulated situation alongside process requirements was performed to achieve quality data collection. The results of the narrative analysis and process observation, combined with a literature review identified widely used Lean tools, wastes and biases that produced a model for the relationships.
Findings
The study established the relationships between bias, Lean tools and wastes which enabled 97.6% error reduction, improved on-time accounting and eliminated three working hours per day. These savings resulted in seven employees being redeployed to new areas with delivery time for products reduced by seven days.
Research limitations/implications
The single site case study with a supporting literature survey underpinning the model would benefit from testing the model in application to different industries and locations.
Practical implications
Application of the model can identify potential relationships between a group of human biases, 25 Lean tools and 10 types of wastes in Lean manufacturing processes that support decision makers and line managers in productivity improvement. The model can be used to identify potential relationships between forms of human biases, Lean tools and types of wastes in Lean manufacturing processes and take suitable remedial actions. The influence of biases and the model could be used as a basis to counter implementation barriers and reduce system-wide wastes.
Originality/value
To the best of the authors’ knowledge, this is the first study that connects the cognitive perspectives of Lean business processes with waste production and human biases. As part of the process, a relationship model is derived.