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Although Total Quality Management (TQM) has been increasingly adopted as a strategic tool for efficient and competitive management of organizations, many of the adopting organizations have failed to achieve the long‐term, substantial gains once deemed possible. While scholars and practitioners blame these failures on numerous causes, most, if not all, can be linked either directly or indirectly to the more general problem of inadequate quality Information Systems (IS). This paper elaborates on the IS role in resolving two critical TQM issues, namely, effective codetermination/coexecution of quality decisions and progress measurement. TQM is information‐intensive and, therefore, IS departments should utilize the powerful tools of information technologies to provide information and capabilities necessary to enable TQM efforts. If IS departments are unwilling or unable to meet the challenge of supporting TQM initiatives, organizations will have to bypass them in their quality journey.

The purpose of this research is to develop a generic framework of a digital twin (DT)-based automated construction progress monitoring through reality capture to extended reality (RC-to-XR).

IDEF0 data modeling method has been designed to establish an integration of reality capturing technologies by using BIM, DTs and XR for automated construction progress monitoring. Structural equation modeling (SEM) method has been used to test the proposed hypotheses and develop the skill model to examine the reliability, validity and contribution of the framework to understand the DRX model's effectiveness if implemented in real practice.

The research findings validate the positive impact and importance of utilizing technology integration in a logical framework such as DRX, which provides trustable, real-time, transparent and digital construction progress monitoring.

DRX system captures accurate, real-time and comprehensive data at construction stage, analyses data and information precisely and quickly, visualizes information and reports in a real scale environment, facilitates information flows and communication, learns from itself, historical data and accessible online data to predict future actions, provides semantic and digitalize construction information with analytical capabilities and optimizes decision-making process.

The research presents a framework of an automated construction progress monitoring system that integrates BIM, various reality capturing technologies, DT and XR technologies (VR, AR and MR), arraying the steps on how these technologies work collaboratively to create, capture, generate, analyze, manage and visualize construction progress data, information and reports.

Construction progress monitoring (CPM) is considered a difficult and tedious task in construction projects, which focuses on identifying discrepancies between the as-built product and the as-planned design. Computer vision (CV) technology is applied to automate the CPM process. However, the synergy between the CV and CPM in literature and industry practice is lacking. This study aims to fulfil this research gap.

A Delphi qualitative approach was used in this study by conducting two interview rounds. The collected data was analysed using manual content analysis.

This study identified seven stages of CPM; data acquisition, information retrieval, verification, progress estimation and comparison, visualisation of the results and schedule updating. Factors such as higher accuracy in data, less labourious process, efficiency and near real-time access are some of the significant enablers in instigating CV for CPM. Major challenges identified were occlusions and lighting issues in the site images and lack of support from the management. The challenges can be easily overcome by implementing suitable strategies such as familiarisation of the workforce with CV technology and application of CV research for the construction industry to grow with the technology in line with other industries.

This study addresses the gap pertaining to the synergy between the CV in CPM literature and the industry practice. This research contributes by enabling the construction personnel to identify the shortcomings and the opportunities to apply automated technologies concerning each stage in the progress monitoring process.

This chapter summarizes issues related to the accurate and timely identification of students with emotional and/or behavioral disorders (EBDs) as well as identifying need, planning interventions, and monitoring outcomes. First, we describe ongoing issues and concerns with accurate (e.g., minimization of false positives and false negatives) and timely (e.g., improved service delivery by being more responsive to students in need of special education) identification of students with emotional disturbance (ED). ¹ Next, we describe general assessment methods and considerations that may contribute to improved service delivery. We close this chapter with a discussion of the critical role that accurate and timely identification plays in the provision of opportunity and the attainment of free appropriate public education (FAPE) mandates.

The purpose of this paper is to propose a framework for the standardisation of the work breakdown structure (WBS) for building projects. This is based on the premise that buildings in general retain basic elemental options, and that there is a commonality of activities in the procurement of building projects.

To achieve the objective, the general practice of developing the WBS is investigated. This is achieved by means of an industry‐wide questionnaire survey designed to identify the most widely used criteria among UK construction organisations in segregating building works into packages. The survey also investigates the sequencing of these criteria across the WBS hierarchy.

The findings reveal that the most frequently used decomposition criteria in the formulation of WBS for building projects are elements, work sections, physical location and construction aids. The proposed framework is presented as a hierarchical decomposition of a building project based on these criteria. It allows for flexibility in level of detail while maintaining a rigid sequencing of the criteria based on their frequency of use.

This paper reports on a specific part of an EPSRC funded project that aims to investigate the application of computer vision techniques to the on‐site measurement of construction progress. The part reported in this paper addresses planning issues that will lead to automatic generation of work packages. Previous studies have focused on automating the planning aspect by associating individual components with schedule information. However, large construction projects usually consist of thousands of components. Planning and tracking progress at the level of the component is unrealistic in these instances. The standardisation framework reported in this paper will form the basis for automating the formulation of work packages, thus providing a uniform basis for tracking progress (based on computer vision) during project execution.

Performance measurement and the balanced scorecard is becoming ubiquitous. However, this paper will argue that some of the early work on performance measurement and management conducted in the early part of the twentieth century has been overlooked by more recent writers. In particular, prediction in today’s literature is not the same concept as that developed by Dr Walter Shewhart in the 1920s. This paper traces the development of performance measurement from its accounting and operational roots until today and concludes that current use of performance measurement could benefit from earlier developments. In particular, the paper argues that the current obsession with testing success maps has limitations as they view the world as being static – relationships holding for all time. The paper proposes that a more dynamic view is taken to these relationships so managers do not become trapped in an outdated strategy map.

This paper aims to serve as a commentary on the paper titled “Implementation of an Adapted Handwriting Without Tears® Programme for Children with Developmental Disabilities in a Special Education Setting.”

It provides an overview of educational strategies that can be used in school settings to support professionals in acquiring skills relevant to their practice and promoting the acquisition of new abilities for their students.

It explores three critical aspects of education: measuring academic progress, using evidence-based methods and enhancing educator training.

This work represents the personal perspective of a professional working in the service delivery field for children with developmental disabilities in schools and rehabilitative centres.

The purpose of this paper is to provide the key dos and don'ts when integrating the people, processes, and systems of companies undertaking mergers and/or acquisitions.

The paper provides the current state of M&A integration across industries, integration dynamics and common pitfalls, integration best practices, and a section regarding how to conduct “merger repair” activities in order to correct integration efforts that have gotten off track.

The measurable impacts of well‐conducted M&A integration efforts is presented and discussed.

Key implications for management who are pursuing a merger and/or acquisition strategy are demonstrated throughout the key success factors described in this paper.

The value to the reader is found in the practical recommendations and tangible actions identified. Likewise, the section describing the need for and how to conduct “merger repair” is new to the literature pertaining to M&A integration.

Progress monitoring and data-based intervention are unique special education developments stemming from efforts to find an effective alternative to diagnostic/prescriptive instruction. Springing from research on Curriculum-based Measurement (CBM) in the late 1970s and early 1980s at the Minnesota Institute for Research on Learning Disabilities, the approach has generated a large body of empirical research and development. While the original work demonstrated that teachers could be more effective using progress monitoring in data-based intervention, most research and development activity has focused on development and extensions of the CBM model with less attention to data-based intervention. While research on progress monitoring has occurred at a high rate, widespread implementation of progress monitoring has been spurred by both federal funding and commercial development. As might be expected, all of this activity has resulted in a large set of successes and disappointments that are described here. For better or worse, as progress monitoring and data-based intervention have been incorporated into Response to Intervention (RTI) models it seems likely that the future of progress monitoring and data-based intervention is tied to the future of RTI. The question is whether this linking will result in adding to the set of successes or to that of disappointments for this unique special education innovation.