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New service businesses carry opportunities for industrial companies. The different cost management and management control implications of those service businesses deserve attention, which is a widely under-researched area in management accounting and control literature. Digital twins could hold potential in unveiling and supporting those new service business opportunities, as a unique approach of this paper. Thus, the purpose of this paper is to examine the possibility and potential for creating a digital twin of a service, especially to unveil the management accounting and control implications of the digital twin in developing new service businesses.

This paper investigates the potential of a digital twin in unveiling cost and control implications of new service businesses by examining the characteristics of a digital twin in the service business development context. The paper use an in-depth interventionist case study, where the designed animations illustrate the possibilities of a digital twin of a service. The animations showing the service process characteristics were first used as a communication tool and eventually those animations were actively used in customer cases for different purposes. This motivated the idea for examining the implications of such animations representing a digital twin of a service.

The paper provides empirical insights regarding the potential for developing and using a digital twin of a service for different cost management and management control purposes. The digital twin of a service may include all main details of a new service offering, simulating the functionality of a service, hence making the performance and the implications of the new service concept clear for all the stakeholders. The digital twin of the service enables defining the processes, setting targets and helps communication about the value generation. Thus, they represent a significant toolkit for the management accounting and control function of the manufacturers.

This paper is among the first attempts to understand the digital twin of the service. The paper is unique in providing financial and control implications of digital twins also in the context of service business development. The in-depth interventionist approach enabled an exceptional exploration process on the subject. The article paves the way toward further research on managing the digital twins of services in the future.

The paper presents the initial groundwork for the development of a research agenda around the management control implications of employing workers with intellectual disability.

The point of departure of this foundational enquiry is primarily prior analyses and critiques of empirical research into the employment of workers with intellectual disabilities.

The authors extend the management control framework advanced by Tessier and Otley (2012) by offering insights relating to the benefits and costs of both compliance as well as performance roles of management control systems (MCS). As such, the authors advocate potential avenues for further empirical investigation and also offer four broad ways in which the use of MCS is implicated in the employment of individuals with an intellectual disability by recognising that achieving compliance outcomes or achieving performance outcomes both carry associated benefits and costs.

The extent to which management control research has engaged with the context of workers with intellectual disability is limited. However, this paper identifies some of the salient considerations underlying an agenda for further research in this area.

The employment of workers with intellectual disabilities is by no means unprecedented. In many Western economies, there have in recent times been significant disability policy shifts, recognising the key role of employment in the financial security and social participation of people with disabilities, including those with intellectual disabilities. A key performance indicator stated in these policy positions is an increase in workforce participation for this group of people. However, an increase in the employment of such individuals is likely to represent significant implications in terms of prevailing conditions as well as new management control configurations that may be required.

The paper overviews existing knowledge about the employment of workers living with an intellectual disability and identifies areas relating to the management control implications of such arrangements within which more research is required.

Recently, interest in sustainability has grown globally in the heavy vehicle and equipment industry (HVEI). However, this industry's complexity poses a challenge to the implementation of generic sustainable supply chain management (SSCM) practices. This study aims to identify SSCM's barriers, practices and performance (BPP) indicators in the HVEI context.

The results are derived from case studies of four multinational manufacturers. Within-case and cross-case analyses were conducted to categorise the SSCM BPP indicators that are unique to HVEI supply chains.

This study's analysis revealed that supply chain cost implications and a deficient information flow between focal firms and supply chain partners are the key barriers to SSCM in the HVEI. This analysis also revealed a set of policies, programmes and procedures that manufacturers have adopted to address SSCM barriers. The most common SSCM performance indicators included eco-portfolio sales to assess economic performance, health and safety indicators for social sustainability and carbon- and energy-related measures for environmental sustainability.

The insights can help HVEI firms understand and overcome the typical SSCM barriers in their industry and develop, deploy and optimise their SSCM strategies and practices. Managers can use this knowledge to identify appropriate mechanisms with which to accelerate their transition into a sustainable business and effectively measure performance outcomes.

The extant SSCM literature has focused on the light vehicle industry, and it has lacked a concrete examination of HVEI supply chains' sustainability BPP. This study develops a framework that simultaneously analyses SSCM BPP in the HVEI.

This paper aims to explore the value that care from a primary mental health care nurse (PMHCN) can bring to people with mental health (MH) problems in health-care delivery.

This study used a focus group of 20 PMHCNs working in primary care (PC) health settings in Saudi Arabia before using thematic content analysis to describe and explore their views and experiences of the integration of MH care into PC units. The researchers used a semi-structured interview format, which began with open-ended probes and proceeded to use of theoretical sampling based on emerging data related to their experiences and perceptions in the integration process.

Four main themes were derived from the thematic analysis of interviews: collaboration, knowledge and experience, awareness and orientation care and influential role.

This study’s use of qualitative research methods has certain limitations, including the small sample size of 20 participants, which means that it may not be representative of all primary MH nurses in primary health-care centers in Saudi Arabia. To make the results applicable to a broader audience, the researcher sought to moderate this limitation by including participants with extensive experience in multiple settings and nurses of different ages.

The cost implications of the PMHCN service are not yet comprehensively understood, but it is apparent that this model is not only regarded extremely positively by MH practitioners but may also have significant benefits in terms of patient outcomes. The configuration of local services and relevant patient demographics will affect the extent to which this study’s findings are transferable. Meanwhile, further research in this area could seek to provide further evidence about the aspects of the PMHCN service model, such as secondary care referrals and waiting times, accident and emergency attendances and patient recovery rates and the impact of providing such a service on health-care practitioners as well as its cost-effectiveness.

This study’s findings suggest that PMHCNs believe that their care improves the quality of PC for patients in PC settings. Elements of the PC placement that professionals particularly valued include their ability to assist patients in their own community and the inclusion of volunteer stakeholders who act as preceptors. The participants expressed a need for improvement of policy related to referrals within the clinics.

A challenge in implementing Universal Design (UD) is the perceived additional cost, which acts as a barrier to its widespread adoption. The few studies that have examined the cost for UD apply a theoretical research approach, failing to account for the unique design context that influences construction costs. This article presents a research methodology to calculate the UD cost in a realistic, context-dependent manner.

To address this gap, “Research-by-Design” is applied in a case study approach involving twelve cases from three typologies: secondary schools, town halls and small retail shops. Two scenarios are compared to the existing situation: (1) “renovating into a 100% inclusive building” and (2) “building fully inclusive right away”.

Although the methodology is time-consuming, it allows for a fair, realistic and detailed comparison between costs in different scenarios and cases. Findings show how financial implications are strongly related to its scale. Both “renovation” and “new build” scenarios involve costs, but these are considerably lower for the latter. “Circulation” and “Exterior stairs and ramps” are among the most expensive to renovate, but have almost no additional cost in the examined cases for the “new build scenario”.

The research methodology presented in this study is time-consuming, which may limit its feasibility for large-scale cost assessments in diverse contexts.

The research methodology proposed in this study provides valuable insights for architects, designers and stakeholders involved in the implementation of UD. It offers a realistic and context-dependent approach to assess the cost implications of UD, enabling informed decision-making during the design and construction phases.

By revealing the specific cost implications of UD in different building contexts, this study contributes to promoting greater accessibility and inclusion in the built environment.

The applied approach distinguishes this study for its ability to provide rich contextual information on actual cost implications for UD. By considering real cases and their unique design contexts, valuable insights are offered into the true costs of implementing UD in the built environment.

The aim of the study has been performed to investigate the relationship between sustainable supply chain management (SSCM) practices and the cost performance of manufacturing firms in Bangladesh. Moreover, this paper highlights the key environment-friendly approaches and their association with financial performance in Bangladesh.

The paper empirically assesses sustainable supply chain performance using four major supply chain practices, including sustainable procurement, sustainable production, sustainable distribution and investment recovery, and compares it with the cost performance. Twenty-four variables were identified through different literature and distributed as a structured questionnaire among the managers appointed in different manufacturing firms in Bangladesh. An empirical study was conducted using the Partial Least Square-Structural Equation Modeling (PLS-SEM) technique to examine the hypothesized relationships.

The results find a positive relationship in two variables of sustainable supply chain practices, including sustainable procurement and investment recovery, while sustainable distribution negatively impacted cost performance. In addition, sustainable production found no effect on cost performance.

The paper emphasizes the financial perspective of a sustainable supply chain without explicit consideration of sustainability's environmental and social dimensions.

This study has implications for the literature on the SSCM approaches of manufacturing firms in the least developed economies. In addition, this study could work as a guideline for some manufacturing industries that prefer a policy or standard to alter their traditional supply chain management system to a sustainable supply chain.

The paper provides a comprehensive framework for evaluating the coordinated effect of SSCM practices on cost performance where variables of four specific activities of SSCM and cost performance are adopted from different studies. Further studies could be initiated, including some other eco-friendly supply chain variables, and the effect could be evaluated from an environmental perspective.

Digital data acquisition is crucial for operations in the digital transformation era. Reality capture (RC) has made an immeasurable contribution to various fields, especially in the built environment. This paper aims to review RC applications, potentials, limitations and the extent to which RC can be adopted for cost monitoring of construction projects.

A mixed-method approach, using Bibliometric analysis and the PRISMA framework, was used to review and analyse 112 peer-reviewed journal articles from the Scopus and Web of Science databases.

The study reveals RC has been applied in various areas in the built environment, but health and safety, cost and labour productivity monitoring have received little or no attention. It is proposed that RC can significantly support cost monitoring owing to its ability to acquire accurate and quick digital as-built 3D point cloud data, which contains rich measurement points for the valuation of work done.

The study’s conclusions are based only on the Scopus and Web of Science data sets. Only English language documents were approved, whereas others may be in other languages. The research is a non-validation of findings using empirical data to confirm the data obtained from RC literature.

This paper highlights the importance of RC for cost monitoring in construction projects, filling knowledge gaps and enhancing project outcomes.

The implementation of RC in the era of the digital revolution has the potential to improve project delivery around the world today. Every project’s success is largely determined by the availability of precise and detailed digital data. RC applications have pushed for more sustainable design, construction and operations in the built environment.

The study has given research trends on the extent of RC applications, potentials, limitations and future directions.

The construction industry has struggled to deliver schemes on time to budget and right-first-time (RFT). There have been many studies into nonconformance and rework through quantitative research over the years to understand why the industry continues to see similar issues of failure. Some scholars have reported rework figures as high as 12.6% of total contract value, highlighting major concerns of the sustainability of construction projects. Separately, however, there have been few studies that explore and detail the views of industry professions who are caught in the middle of quality issues, to understand their perceptions of where the industry is failing. As such, this paper interrogates qualitative data (open-ended questions) on the topic of nonconformance and rework in construction to understand what industry professionals believe are the causes and suggested improvement areas.

A qualitative approach is adopted for this research. An industry survey consisting of seven open-ended questions is presented to two professional working groups within a Tier 1 contractor, and outputs are analysed using statistic software (NVivo 12) to identify prominent themes for discussion. Inductive analysis is undertaken to gain further insight into responses to yield recurrent areas for continuous improvement.

Qualitative analysis of the survey reveals a persistent prioritisation of cost and programme over quality management in construction project. Furthermore, feedback from construction professionals present a number of improvement areas that must be addressed to improve quality. These include increased training and competency investment, overhauling quality behaviours, providing greater quality leadership direction and reshaping the way clients govern schemes.

There are limitations to this paper that require noting. Firstly, the survey was conducted within one principal contractor with varying levels of knowledge across multiple sectors. Secondly, the case study was from one major highways scheme; therefore, the generalisability of the findings is limited. It is suggested that a similar exercise is undertaken in other sectors to uncover similar improvement avenues.

The implications of this study calls for quality to be re-evaluated at project, company, sector and government levels to overhaul how quality is delivered. Furthermore, the paper identifies critical learning outcomes for the construction sector to take forward, including the need to reassess projects to ensure they are appropriately equip with competent personnel under a vetted, progressive training programme, share collaborative behaviours that value quality delivery on an equal standing to safety, programme and cost and tackle the inappropriate resource dilemmas projects finding themselves in through clear tendering and accurate planning. In addition, before making erratic decisions, projects must assess the risk profiling of proceed without approved design details and include the client in the decision-making process. Moreover, the findings call for a greater collaborative environment between the construction team and quality management department, rather than being seen as obstructive (i.e. compliance based policing). All of these must be driven by leadership to overhaul the way quality is managed on schemes. The findings demonstrate the importance and impact from open-ended survey response data studies to enhance quantitative outcomes and help provide strengthened proposals of improvement.

This paper addresses the highly sensitive area of quality failure outcomes and interrogates them via an industry survey within a major UK contractor for feedback. Unique insights are gained into how industry professionals perceive quality in construction. From previous research, this has been largely missing and offers a valuable addition in understanding the “quality status quo” from those delivering schemes.

This study evaluates the effect of transparency measures on public procurement efficiency, focusing on Thailand’s Infrastructure Transparency Initiative (CoST). This study aims to understand its impact on the country’s public infrastructure procurement practices.

This paper analyses Thailand’s government construction procurement data, focusing on budgetary savings and CoST process participation. Budgetary savings are this study dependent variable, while the main intervention variable is the adoption of the CoST data disclosure standard. This study uses multiple linear regression, fixed-effects model and propensity score matching with the logit model for a comprehensive analysis.

This study shows that using the CoST data disclosure leads to notable budget savings in Thai public construction procurement. With CoST’s introduction, the savings rose by Baht 9.6m, and even with added controls, the savings remained significant at around Baht 3.3m. The savings consistently stay near 5% across different models. The propensity score matching method confirms these results, consistent with factors such as open bidding and agency categorisation.

This study might not capture all benefits, especially non-financial ones. Thailand’s unique context and potential biases in data sources also need consideration.

CoST evidence backs Thailand’s procurement transparency. This study recommends broadening CoST, streamlining online platforms and promoting digital public engagement. Training stakeholders and partnering with state-owned enterprises and local agencies is vital to align with CoST and mitigate risks.

This study shows a clear link between transparency from information disclosure and budget efficiency in public procurement, using data from Thailand. It highlights the potential of transparency measures in developing countries.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.