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This study applied the lean approach to the reinforcement work process in the component production of industrialised building system precast concrete construction (IBSPCC). The purpose of this paper is to identify and eliminate non-value added (NVA) activities to enhance the efficiency of the production process.

Data were collected via a case study of six-storey precast concrete building. A mapping of the reinforcement work process was conducted based on observations using time study technique and time-lapsed video, complemented by semi-structured interviews.

Through this application, several NVA activities, such as unnecessary inventory, excessive movement and coordination issues, were identified. Production performance could be enhanced by implementing Just-in-Time, Kanban, and layout improvements, which would address NVA activities.

Due to the complexity of the construction process, only specific process elements were observed. To map the complete process, comprehensive observation must be conducted from beginning to end, which, though worthwhile, would be very time and resource intensive.

This paper focusses on strategies for improving the efficiency of the IBSPCC production process in Malaysian construction by developing a conceptual framework of the lean approach for the reinforcement work process. Certain aspects in the process such as layout and inventory need to be redesigned and simplified by minimising NVA activities.

This feasibility study originated from a request from a high‐quality confectionery manufacturer and retailer for research into the possibility of assessing the interaction of multiple outlets in the same town. The particular problem was that of estimating pedestrian flow patterns so that the siting of new outlets would not attract business away from existing outlets of the same company. Various methods of collecting pedestrian data were reviewed, and for reasons of cost and practicality it was decided to concentrate on tracking (105 city‐centre trips) and point‐counting methods. Time‐lapse photography was used for point counting, being the only method capable of handling the volume of pedestrians (7,267). A number of computer programs were written which allowed the photographic data to be transformed into a network flow model. A full‐scale test of the model was made using data collected by Nottingham City Council for a network of 57 links.

Recognising the as-built state of construction elements is crucial for construction progress monitoring. Construction scholars have used computer vision-based algorithms to automate this process. Robust object recognition from indoor site images has been inhibited by technical challenges related to indoor objects, lighting conditions and camera positioning. Compared with traditional machine learning algorithms, one-stage detector deep learning (DL) algorithms can prioritise the inference speed, enable real-time accurate object detection and classification. This study aims to present a DL-based approach to facilitate the as-built state recognition of indoor construction works.

The one-stage DL-based approach was built upon YOLO version 4 (YOLOv4) algorithm using transfer learning with few hyperparameters customised and trained in the Google Colab virtual machine. The process of framing, insulation and drywall installation of indoor partitions was selected as the as-built scenario. For training, images were captured from two indoor sites with publicly available online images.

The DL model reported a best-trained weight with a mean average precision of 92% and an average loss of 0.83. Compared to previous studies, the automation level of this study is high due to the use of fixed time-lapse cameras for data collection and zero manual intervention from the pre-processing algorithms to enhance visual quality of indoor images.

This study extends the application of DL models for recognising as-built state of indoor construction works upon providing training images. Presenting a workflow on training DL models in a virtual machine platform by reducing the computational complexities associated with DL models is also materialised.

In Vulcan 2 and Vulcan 3 I established the fact that every physical skill is a job‐relevant sensori‐motor activity. Some confusion is introduced when people start talking about sensori‐motor skills. Not all people mean the same thing when they use the term sensori‐motor skill. The purist — a rare enough bird anyway in the training business — would mean any activity with sensory and motor elements, no matter how simple or common they were. However the term has come to have a special meaning: some skill with some advanced or unusual sensory element or some unusual, rare, refined motor element or both, not found in the normal domestic skill repertoire. On a strict use of words all skills are sensori‐motor but one has to bow before the storm of common usage and accept the term sensori‐motor skill as meaning a skill with advanced sensory and/or motor elements. In order to avoid confusion, as far as this is possible, I prefer to call this type of skill an advanced sensori‐motor skill to mean that it has something unusual in one or both of the elements.

The flexibility of managers to respond to risk and uncertainty inherent in business decisions is clearly of value. This value has historically been recognized in an ad hoc manner in the absence of a methodology for more rigorous assessment of value. The application of real option methodology represents a more objective mechanism that allows managers to hedge against adverse effects and exploit upside potential. Of particular interest to managers in the merger and acquisition (M&A) process is the value of such flexibility related to the particular terms of a transaction. Typically, stock for stock transactions take more time to complete as compared to cash given the time lapse between announcement and completion. Over this period, if stock prices are volatile, stock for stock exchanges may result in adverse selection through the dilution of shareholder wealth of an acquiring firm or a target firm.

The paper develops a real option collar model that may be employed by managers to measure the market price risk involved to their shareholders in offering or accepting stock. We further discuss accounting issues related to this contingency pricing effect. Using an acquisition example from U.S. banking industry we illustrate how the collar arrangement may be used to hedge market price risk through flexibility to renegotiate the deal by exercising managerial options.

Involvement of lenders for PPP highway projects in India starts after the bid award. The post-award development phase of Toll and Annuity PPPs differ significantly in terms of potential risk assumed by lenders. This study aims to assess the impact of the transparency law on the post-award development phase of Toll and Annuity PPPs.

A unique dataset of 469 PPP highway projects implemented in India was used to conduct this empirical study. An OLS regression model was developed to assess the impact of the transparency law on the post-award development phase.

Enacting the transparency law increased the duration of the post-award development phase of Toll projects; however, its impact on Annuity projects was not significant. Moreover, Toll and Annuity projects with a longer post-award development phase had a shorter construction phase. The post-award development phase of the Toll projects was relatively more sensitive to technical, economic and location-specific variables than Annuity projects. Length of road stretch, duration of the concession period and individual income of end-users significantly impacted the duration of this phase of Toll projects.

Transparency law can improve risk mitigation of Toll projects during the post-award development phase.

The impact of transparency law on PPP projects has never been assessed. This study assesses its impact on the two forms of PPPs. It also highlights the determinants of this phase and how they differ for the two forms of PPPs.

This study explores the relevance of the value chain concept in internet‐driven business and assesses the extent to which businesses utilize the internet from a value chain perspective. It attempts to answer the following three questions: is the value chain concept relevant and applicable to the internet as a means of understanding the internet? To what extent do organizations utilize the internet according to a value chain perspective? Does the business use of the internet change over time?

To answer these questions, a longitudinal survey study was conducted over a two‐year period. The first study collected data from 110 firms on the way they utilize the internet. Two years later, a similar survey was conducted with 70 firms using the same instrument used in the first study.

The study provided empirical support for the use of the value chain concept as a viable taxonomy for assessing the level of adoption of the internet. The study also provided a time‐lapsed glimpse of how organizations evolve in adopting the internet.

One of the shortcomings of the study is in the sampling process, although various measures were taken to ensure that the data represent a wide range of organizations, so that the findings can be reasonably generalizable.

The most important practical contribution of the study is that it provides practitioners with a tool to systematically plan and deploy an ever‐increasing array of internet applications. The internet value chain model should provide organizations with a strategic and macro perspective to evaluate and manage various internet applications.

An important contribution of this study is that it empirically observed the evolution of the internet practices in business according to the value chain framework. There has been plenty of anecdotal evidence of changes in the way business utilizes the internet, but no study has empirically assessed these changes systematically based on a theoretical framework. The study provides a valuable theoretical framework for researchers to continuously accumulate knowledge on the use of the internet in business.

Reports on survey‐behavioural research in a major and fundamental development ‐ the Questronic project based at the University of Sheffield (UK), and its first product, the Ferranti Market Research Terminal (MRT). States that the MRT is a battery‐operated, hand‐held data‐capture terminal and it is a replacement for the usual questionnaire necessity ‐ clipboard and pencil. Describes the MRT and its functions including keyboard and electronic storage, so aiding survey research, both economic and operational. Lists out the operations and benefits in detail enabling the user a fast, modern aid for use with questionnaires. Goes on to give further developing procedures and includes a contact address for further information regarding the importance of development MRT routines in survey research.

The purpose of this paper is to improve the understanding of the impact of mass timber construction methods on construction performance through the successful delivery of the first-of-a-kind tall wood building, Brock Commons Tallwood House (Tallwood House). This paper is one of a set of papers examining the project; companion papers describe innovations used during the mass timber design and construction processes.

A mixed-method, longitudinal case study approach was used in this research project to investigate and document the Tallwood House project. Quantitative data were collected to perform the following analysis: hook time, the variability of productivity and schedule reliability. Members of the research team observed construction progress, meetings and decision-making, conducted periodic interviews and reviewed project artifacts.

The research presented in this paper is the culmination of a longitudinal study aimed at studying the innovation process on a project where radical innovations of structural systems were developed. Prefabrication, combined with the use of a virtual design and construction (VDC) model for planning and fabrication and early collaboration with trades, construction managers and consultants, increased the labor productivity of the on-site erection of the mass timber structural components and envelope panels and expedited the construction schedule.

This paper details an in-depth investigation into the construction productivity for a unique building project and lessons learned. The case study chosen is the construction of Tallwood House at the University of British Columbia. Tallwood House was the tallest mass-timber hybrid building in the world at the time of its construction.

The study aims to develop measures for innovation effectiveness impacting organizational performance outcomes. Substantial evidence suggests that measuring innovation effectiveness (IE) continues to be challenging because of the use of different measures across innovation’s broad spectrum. The purpose of this study is to overcome it by examining multiple drivers of IE in emerging market economies (EMEs) and predicting their impact on financial and nonfinancial performance outcomes.

Through a two-wave panel design, firms from India, Oman and the United Arab Emirates participated in the study with a time lapse of 12 months (T1n = 417, T2n = 403). Four cross-lagged competing models are tested for autoregressive, causal, reversed and reciprocal effects using structural equation modeling (SEM).

The findings show that the synergistic effect of multiple innovation characteristics, such as innovation degree, cost, frequency and speed determines its endogenous effectiveness. The exogenous effectiveness of innovation is further established through its impact on financial and nonfinancial performance outcomes. Furthermore, readiness for innovation (RFI) is a critical factor that moderates the relationship between drivers and IE.

The study’s findings could inform practitioners in emerging market economies about the appropriate measures of IE. It will guide managerial decisions on making an investment, evaluation, accountability and strategic choices related to innovation.

It is one of the first studies that use a time-based lens to examine IE in EMEs. It posits that given the innovation’s complexity, IE needs to be measured at multiple levels. The study explains how evolutionary dynamics in different sociocultural contexts can bring a new perspective into theory of diffusion of innovation. The moderating role of RFI brings new insights into the IE process and emphasizes its importance in objective-driven and performance-focused innovation efforts.