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The purpose of this article is to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the analysis of variance (ANOVA) application after the preliminary test on the model specification.

A new approach is proposed to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the ANOVA application. First, we determine this relationship from the general perspective of Six Sigma methodology under the normality assumption. Then, the approach is extended to a balanced two-stage nested design with a random effects model in which a preliminary test is used to fix the main test statistic.

The features of mean-shifted and inflated (but centred) processes with the same specification limits from the perspective of Six Sigma are studied. The shift and inflation coefficients are derived for the two-stage balanced ANOVA model. We obtained good predictions for the process shift, given the inflation coefficient, which has been demonstrated using numerical results and applied to case studies. It is understood that the proposed method may be used as a tool to obtain an efficient variance estimator under mean shift.

In this work, as a new research approach, we studied the link between mean shift and inflation coefficients when the underlying null hypothesis is rejected in the ANOVA. Derivations for these coefficients are presented. The results when the null hypothesis is accepted are also studied. This needs the help of preliminary tests to decide on the model assumptions, and hence the researchers are expected to be familiar with the application of preliminary tests.

After studying the proposed approach with extensive numerical results, we have provided two practical examples that demonstrate the significance of the approach for real-time practitioners. The practitioners are expected to take additional care before deciding on the model assumptions by applying preliminary tests.

The proposed approach is original in the sense that there have been no similar approaches existing in the literature that combine Six Sigma and preliminary tests in ANOVA applications.

Some BIM implementation strategies are critical, while others are insignificant and ineffective in terms of lowering BIM adoption obstacles and promoting widespread acceptance of BIM in projects. The BIM literature has not provided evidence to support this claim or identify the fundamental BIM implementation strategies. This study filled this gap by identifying and investigating the effect of fundamental BIM implementation methodologies on the occurrence of proportional impacts between stages.

The findings indicate a positive and crucial relationship between the stages of the BIM implementation strategies and the reduction of barriers (r = 1.79, z = 2.15), preliminary and sustained BIM adoption barriers (r = 1.53, z = 60.83), BIM adoption on projects and BIM-enabled integration and collaboration (r = 0.7, z = 2.74). This validates the model's hypotheses and demonstrates that the fundamental BIM implementation strategies will accelerate the reduction of BIM adoption hurdles. The impact, however, will be the same for both sustained and preliminary barriers. This implies that lowering the obstacles alone will not secure BIM adoption.

The validation of the model's hypotheses demonstrated that the fundamental BIM implementation strategies will accelerate the reduction of BIM adoption hurdles. The impact, however, will be the same for both sustained and preliminary barriers. This implies that lowering BIM adoption obstacles alone will not secure BIM adoption. This study proposes that BIM deployment tactics be carefully chosen in order to remove preliminary impediments, reduce barriers and energise BIM acceptance.

In line with the findings of this study, BIM adoption must be consistent and long-term before the benefits in project execution become evident and substantiated. The BIM abilities of project participants, the feasibility of BIM conventions and the proficiency of BIM supervisors may all play a role in this.

This research implies a few approaches and tactics for implementing BIM in an efficient and beneficial manner. The study's findings imply that BIM deployment tactics should be carefully chosen in order to remove preliminary impediments, reduce barriers and energise BIM acceptance. It also explains how to structure BIM implementation strategies in developing countries. Another significant practical implication is the model's conclusion on the benefits of BIM adoption.

This study emphasises the significance of understanding the interrelatedness between the stages of the BIM implementation process in order to promote unavoidable and high-quality BIM adoption, as well as identifying the essential strategies that will guide policymakers and industry players in improving and pursuing successful BIM implementation. This study adds to BIM implementation theories by providing new information on the models, stages and interconnections of the BIM implementation process. However, the study could not identify the factors that impede BIM adoption despite the reduction in barriers and use of fundamental BIM implementation strategies.

This study aims to design and validate a decision support system (DSS), named preliminary risk assessment of brownfield sites (PRABS). It is intended that the proposed DSS will aid the identification of potential hazards and, in doing so, highlight challenges facing those stakeholders dealing with the decision-making on brownfield site redevelopments, where the examples of diverse stakeholders would include, for instance, risk assessors, local planning authorities, regulator, developers, civil engineers, architectures, landowners, investors and alike. Moreover, the DSS will enable them to promote safer redevelopment and minimise the risks to future occupants of brownfield sites and neighbouring lands, on the top of the tool being communal platform of an effective communication between them as it is for both experts and non-experts.

This research employs a comprehensive five-stage process, integrating both quantitative and qualitative methods and utilizing mixed methods for a nuanced exploration of data. The initial stage involves an in-depth examination of contemporary risk assessment tools for contaminated sites, setting the foundation and benchmarks for subsequent stages. Stage two focuses on creating a conceptual framework using insights from existing literature to guide the development of the DSS tool. Stage three introduces a validation mechanism through a questionnaire administered to experts. Stage four involves the active development of the DSS tool, transforming theoretical constructs into a practical application. The final stage, stage five, employs quantitative data analysis and case studies to validate, refine and enhance the DSS tool’s applicability in real-world scenarios, ensuring its approval.

This study presents PRABS, a user-friendly DSS for the PRABS. Validation through a quantitative online survey indicates strong support for PRABS, with around 80% of participants willing to recommend it due to its ease of use and information quality. Qualitative data analysis using real-life case studies further demonstrates the tool’s effectiveness. PRABS proves valuable in identifying hazards during the preliminary stage, accurately predicting potential contaminants despite limited input data in the case studies. The tool’s hazard identification aligns well with expert judgments and case study reports, confirming its practical utility.

This study has several limitations. First, the DSS identifies only hazards associated with one layer of site geology, even though sites may include multiple layers, which limits the comprehensiveness of the hazard identification process. Second, adopting an online survey approach posed challenges in achieving a high response rate and gathering a representative sample, making it uncertain how the results might vary with a higher number of professional participants. This limitation affects the generalisability of the findings. Finally, while this study identified 65 potential hazards associated with brownfield sites, this number could be expanded to include hazards related to plants, animals and air, indicating the need for a more inclusive approach to hazard identification. Given these limitations, future research should focus on addressing these gaps.

The contributions of this study offer practical benefits. Firstly, it enables the initial risk assessment process to be more comprehensive and integrated and reduces complexity in the risk assessment process by ensuring that all probabilities, along with their significance, are identified at the initial stage of the risk assessment. This could be a strong starting point for successfully conducting a more detailed risk assessment and remediation. Secondly, the developed PRABS can promote effective environmental communication among stakeholders, which should speed up the planning process and help develop brownfield sites more efficiently and effectively, while preserving the natural environment.

Audit trail cost management is crucial for ensuring accountability and enhancing quality assurance in construction management. Despite limited practical studies on audit trail management from a cost perspective; this study developed a lifecycle-based audit trail cost management framework. It used synchronized Building Information Modeling (BIM) cost models and Bills of Quantities (BoQs) to address the existing gap.

This study employed a descriptive case study approach of a real-life hospital project in China. Data triangulation was achieved through interviews, observations, documents, and relevant artifacts.

The study identified three key factors contributing to cost variances between BIM cost models and BoQs: differences in measurement rules, model precision, and professional errors, particularly evident during the preliminary estimate stage. Notably, significant cost savings of approximately RMB 5.811 million were achieved during the detailed estimate stage. During the construction phase, a synchronized approach was deployed to improve precise payment verification and modifications to the BIM model. In the post-construction phase, the synchronized as-built BIM models and BoQs served as primary references to facilitate the resolution of operational discrepancies.

The research contributes to the literature by proposing a synchronized approach of BIM cost models and BoQs. This approach enhances traceability and accountability of project information, catering to the digitalization needs of the construction industry.

This study unveils a pragmatic approach to enhancing transparency and accountability in audit-trail cost management by synchronizing BIM cost models and BoQs at various project stages. The synchronized approach offers a promising direction for future research and implementation of audit trail frameworks to enhance cost management in construction.

Business analytics (BA) is a new frontier of technology development and has enormous potential for value creation. Information systems research shows ample evidence of its positive business impacts and organizational performance. However, there is limited understanding of how decision-makers or users of BA outcomes actually engage with data analysts in the process of data-driven insight generation and how they improve their understanding of business environments using BA outcomes. To aid this engagement and understanding, this study investigates the interaction between decision-makers and data analysts when they attempt to uncover data capacities and business needs and acquire business insights from BA tools.

This study employs an interpretive field study with thematic analysis. The authors conducted interviews with 31 participants who all relied on BA in their daily decisions. The study participants were engaged in different BA roles, including data analysts and decision-makers. They validated the applicability and usefulness of our findings through a focus group with eight practitioners, including decision-makers and data analysts from the same companies.

This study proposes a process model of data-driven sensemaking and sensegiving based on Weick’s sensemaking framework. The findings exhibit that decision-makers are engaged in sensemaking by identifying areas of focus, determining BA scope, evaluating generated insights and turning BA into action. The findings also show that data analysts engage in sensemaking by consolidating data, data understanding, preparing preliminary outcomes and generating actionable reports. This study shows how sensemaking processes and sensegiving activities work together over time through immediate enactment, selection and decision cycles.

This study is a first attempt to understand interactions in the context of BA using the perspective of sensemaking and sensegiving.

Due to the complexity and diversity of megaprojects, the architectural programming process often involves multiple stakeholders, making decision-making difficult and susceptible to subjective factors. This study aims to propose an architectural programming methodology system (APMS) for megaprojects based on group decision-making model to enhance the accuracy and transparency of decision-making, and to facilitate participation and integration among stakeholders. This method allows multiple interest groups to participate in decision-making, gathers various perspectives and opinions, thereby improving the quality and efficiency of architectural programming and promoting the smooth implementation of projects.

This study first clarifies the decision-making subjects, decision objects, and decision methods of APMS based on group decision-making theory and value-based architectural programming methods. Furthermore, the entropy weight method and fuzzy TOPSIS method are employed as calculation methods to comprehensively evaluate decision alternatives and derive optimal decision conclusions. The workflow of APMS consists of four stages: preparation, information, decision, and evaluation, ensuring the scientific and systematic of the decision-making process.

This study conducted field research and empirical analysis on a practical megaproject of a comprehensive transport hub to verify the effectiveness of APMS. The results show that, in terms of both short-distance and long-distance transportation modes, the decision-making results of APMS are largely consistent with the preliminary programming outcomes of the project. However, regarding transfer modes, the APMS decision-making results revealed certain discrepancies between the project's current status and the preliminary programming.

APMS addresses the shortcomings in decision accuracy and stakeholder participation and integration in the current field of architectural programming. It not only enhances stakeholder participation and interaction but also considers various opinions and interests comprehensively. Additionally, APMS has significant potential in optimizing project performance, accelerating project processes, and reducing resource waste.

Policing requires atypical work hours. The present study examined associations between shiftwork and pregnancy loss among female police officers.

Participants were 91 female officers with a prior history of at least one pregnancy. Shiftwork information was assessed using daily electronic payroll work records. Any prior pregnancy loss (due to miscarriage) was self-reported. Logistic regression estimated odds ratios (OR) and 95% confidence intervals (CI) for main associations.

On average, the officers were 42 years old, had 14 years of service, and 56% reported a prior pregnancy loss. Officers who worked dominantly on the afternoon or night shift during their career had 96% greater odds of pregnancy loss compared to those on day shift (OR = 1.96, 95% CI:0.71–5.42), but the result was not statistically significant. A 25% increase in percent of hours worked on night shift was associated with 87% increased odds of pregnancy loss (OR = 1.87, 95% CI:1.01–3.47). Associations were adjusted for demographic and lifestyle factors. Objective assessment of shiftwork via electronic records strengthened the study. Limitations include small sample size, cross-sectional design and lack of details on pregnancy loss or the timing of pregnancy loss with regard to shiftwork.

The present study is preliminary and cross-sectional.

With considerable further inquiry and findings into this topic, results may have an impact on police policy affecting shift work and pregnant police officers.

Implication on the health and welfare of police officers.

To our knowledge, there are no empirical studies which associate shiftwork and pregnancy loss among police officers. This preliminary study suggested an association between shiftwork and increased odds of pregnancy loss and points out the need for further study.

Construction professionals are the major contributors to developing a sustainable construction industry, whereas architects, engineers and quantity surveyors are the key construction professionals who must play extraordinary roles in achieving better sustainable construction. Therefore, this study aims to identify the job attributes of key Sri Lankan construction professionals in addressing challenges associated with climate change.

The study adopted a mixed research approach. A literature review and preliminary semi-structured interviews were used to appraise the job roles of architects, engineers and quantity surveyors in addressing challenges associated with climate change. The data collected through the qualitative approach were used in an online questionnaire survey, and the findings were analysed using the relative index method.

The findings highlight that regardless of the knowledge of the professional category on green rating tools, carbon footprint, adaptation of renewable energies for the reduction of energy consumption, building information modelling-related applications and waste management concepts/practices are the foremost job attributes required for the key Sri Lankan construction professionals in addressing challenges associated with climate change.

The results from this study provide a handful of guidance to construction industry professionals, national and international professional institutions, non-governmental organisations and other relevant authorities to address climate change within the built environment by identifying ways for improving the relevant key job attributes of construction industry professionals.

To the best of the authors’ knowledge, this is the first study that explores the job attributes of key Sri Lankan construction professionals in addressing the challenges associated with climate change.

This investigation serves a dual purpose: providing preliminary results and serving as a pilot study to confirm the viability of the hypotheses advanced towards a full-scale study. This paper aims to present the preliminary findings of an investigation that explored the constructs of personality traits and situational crime prevention theory (SCPT) as antecedents to social cognitive determinants (attitude, perceived behavioural control and subjective norms using the theory of planned behaviour [TPB] framing) and how these elements subsequently estimate compliant information security behaviour. Moreover, this paper delves into the contrasting influences of light and dark personality traits on insider information security compliance.

A cross-sectional survey was conducted to study SCPT measures and the personality factors dyad using a diverse but limited sample (n = 82).

There were ten significant direct relationships between SCPT factors and personality traits related to the components of the TPB. Seventeen hypotheses were not supported. However, these findings highlight the complexity of the topic under study.

Understanding individual differences within the compliance model could be used for custom training protocols, employee selection, assignment and specific types of information security interventions.

There is a scarcity of studies considering the effects of situational and personality factors, specifically the dark versus light triad of personality traits within the information security domain. Therefore, this preliminary result provides early insight that could guide further studies. This research could have important implications for organisations at risk of insider attacks.

The accurate prediction of driving torque demand is essential for the development of motion controllers for mobile robots on complex terrains. This paper aims to propose a hybrid model of torque prediction, adaptive EC-GPR, for mobile robots to address the problem of estimating the required driving torque with unknown terrain disturbances.

An error compensation (EC) framework is used, and the preliminary prediction driving torque value is achieved using Gaussian process regression (GPR). The error is predicted using a continuous hidden Markov model to generate compensation for the prediction residual caused by terrain disturbances and uncertainties. As the final step, a gain coefficient is used to adaptively tune the significance of the compensation term through parameter resetting. The proposed model is verified on a sample set, including the driving torque of a mobile robot on three different sandy terrains with two driving modes.

The results show that the adaptive EC-GPR yields the highest prediction accuracy when compared with existing methods.

It is demonstrated that the proposed model can predict the driving torque accurately for mobile robots in an unconstructed environment without terrain identification.