Voice Assisted Key-In Building Quantities Estimation System

Voice recognition technology has been in existence over several decades but its application in the construction industry has been minimal. Despite the several advantages it offers, its application has been limited to smart building integration only. This study has made a significant contribution by integrating voice recognition technology into key-in building quantities estimation software. The Visual Basic programming language was used to design and code the interface of the voice recognition system and key-in estimating software model. The prototype model continues to have some challenges because it cannot work efficiently in a noisy work environment and there is limited range of vocabulary it can recognize. This paper seeks to challenge the stakeholders of the construction industry to maximize the benefits of voice recognition technology and integrate it into other construction tasks. In addition, future research can consider integrating building information modeling and voice recognition technology

Modelling the Impact of Building Information Modelling (BIM) Implementation Drivers and Awareness on Project Lifecycle

The Architecture, Engineering, Construction and Operations (AECO) industry is generally slow in adopting emerging technologies, and such hesitance invariably restricts performance improvements. A plethora of studies have focused on the barriers, Critical Success Factors (CSFs), lifecycle and drivers independently, but none have explored the impact of BIM drivers and awareness on the project lifecycle. This study empirically explored the impact of BIM drivers and awareness on the project lifecycle using Structural Equation Modelling (SEM). Initially, a conceptual model was developed from an extensive literature review. Thereafter, the model was tested using primary questionnaire data obtained from 90 construction professionals in Lagos, Nigeria. Emergent findings indicate that Building Information Modelling (BIM) drivers have a high impact on BIM awareness at the operation stage of the project lifecycle. The SEM model has an average R2 value of 23% which is moderate. Consequently, this research contributes to the existing body of knowledge by providing invaluable insight into the impact of BIM drivers on BIM awareness in the project lifecycle. Knowledge acquired will help industry stakeholders and government to develop appropriate policies to increase BIM uptake within contemporary practice

Building Information Modeling Execution Drivers for Sustainable Building Developments

The need for continuous global improvement in the construction industry’s current state is inevitable. This pursuit for advancement is to benefit all concerned stakeholders in the construction industry, and innovation has been acknowledged as this improvement measure. Interestingly, Building Information Model (BIM) is a typical example of such innovation in the construction industry. It circumvents human errors, lessening project costs, strengthening productivity and quality, and reducing the project delivery time. This analysis investigates the factors influencing BIM implementation in construction in developing nations. A comprehensive literature review was performed to determine what factors contribute to BIM adoption. These drivers were categorized using exploratory factor analysis (EFA). Partial Least Square Structural Equation Modeling (PLS-SEM) was also used with a questionnaire survey of 100 Nigerian building engineering professionals. Findings from the model highlight the most critical drivers of sustainable BIM deployment. The study’s conclusion will serve as a guideline for policymakers in developing nations that want to finish successful projects by avoiding BIM implementation drivers and improving the accomplishment of building projects via the usage of BIM

A Mathematical Analysis of 4IR Innovation Barriers in Developmental Social Work—A Structural Equation Modeling Approach

The fourth industrial revolution (4IR) era also known as digital age is central to the advancement of the construction industry as the industry is currently facing a myriad of challenges, including poor productivity and project failure. Therefore, there is an urgent need for industry to adopt 4IR innovations to increase the building business’s performance. The study explored the relationship between the critical barriers to 4IR innovations to foster sustainable development. The study embraced a numerical exploration approach which employed a questionnaire to obtain information from building industry experts. The questionnaire data were used to classify the 4IR barriers into policy and structure, readiness, and acquisition, using Exploratory Factor Analysis (EFA). Likewise, a predictive model was developed using Structural Equation Modelling-Partial Least Square (SEM-PLS). It explained the relationship between the barrier categories and the barriers to 4IR innovation adoption for sustainable development. The results showed that policy and structure were critical components of 4IR adoption that the stakeholders of the construction industry must pay close attention to. The study also provided valuable areas for future research to enhance 4IR innovation adoption for sustainable development

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P < 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)