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Heating, ventilating, air-conditioning and cooling (HVAC) systems are crucial in daily health-care facility services. Design-related defects can lead to maintenance issues, causing service disruptions and cost overruns. These defects can be avoided if a link between the early design stages and maintenance feedback is established. This study aims to use experts’ experience in HVAC maintenance in health-care facilities to list and evaluate the risk of each maintenance issue caused by a design defect, supported by the literature.

Following semistructured interviews with experts, 41 maintenance issues were identified as the most encountered issues. Subsequently, a survey was conducted in which 44 participants evaluated the probability and impact of each design-caused issue.

Chillers were identified as the HVAC components most prone to design defects and cost impact. However, air distribution ducts and air handling units are the most critical HVAC components for maintaining healthy conditions inside health-care facilities.

The unavailability of comprehensive data on the cost impacts of all design-related defects from multiple health-care facilities limits the ability of HVAC designers to furnish case studies and quantitative approaches.

This study helps HVAC designers acquire prior knowledge of decisions that may have led to unnecessary and avoidable maintenance. These design-related maintenance issues may cause unfavorable health and cost consequences.

Occupant behavior can lead to considerable uncertainties in thermal comfort and air quality within buildings. To tackle this challenge, the use of probabilistic controls to simulate occupant behavior has emerged as a potential solution. This study seeks to analyze the performance of free-running households by examining adaptive thermal comfort and CO2 concentration, both crucial variables in indoor air quality. The investigation of indoor environment dynamics caused by the occupants' behavior, especially after the COVID-19 pandemic, became increasingly important. Specifically, it investigates 13 distinct window and shading control strategies in courtyard houses to identify the factors that prompt occupants to interact with shading and windows and determine which control approach effectively minimizes the performance gap.

This paper compares commonly used deterministic and probabilistic control functions and their effects on occupant comfort and indoor air quality in four zones surrounding a courtyard. The zones are differentiated by windows facing the courtyard. The study utilizes the energy management system (EMS) functionality of EnergyPlus within an algorithmic interface called Ladybug Tools. By modifying geometrical dimensions, orientation, window-to-wall ratio (WWR) and window operable fraction, a total of 465 cases are analyzed to identify effective control scenarios. According to the literature, these factors were selected because of their potential significant impact on occupants’ thermal comfort and indoor air quality, in addition to the natural ventilation flow rate. Additionally, the Random Forest algorithm is employed to estimate the individual impact of each control scenario on indoor thermal comfort and air quality metrics, including operative temperature and CO2 concentration.

The findings of the study confirmed that both deterministic and probabilistic window control algorithms were effective in reducing thermal discomfort hours, with reductions of 56.7 and 41.1%, respectively. Deterministic shading controls resulted in a reduction of 18.5%. Implementing the window control strategies led to a significant decrease of 87.8% in indoor CO2 concentration. The sensitivity analysis revealed that outdoor temperature exhibited the strongest positive correlation with indoor operative temperature while showing a negative correlation with indoor CO2 concentration. Furthermore, zone orientation and length were identified as the most influential design variables in achieving the desired performance outcomes.

It’s important to acknowledge the limitations of this study. Firstly, the potential impact of air circulation through the central zone was not considered. Secondly, the investigated control scenarios may have different impacts on air-conditioned buildings, especially when considering energy consumption. Thirdly, the study heavily relied on simulation tools and algorithms, which may limit its real-world applicability. The accuracy of the simulations depends on the quality of the input data and the assumptions made in the models. Fourthly, the case study is hypothetical in nature to be able to compare different control scenarios and their implications. Lastly, the comparative analysis was limited to a specific climate, which may restrict the generalizability of the findings in different climates.

Occupant behavior represents a significant source of uncertainty, particularly during the early stages of design. This study aims to offer a comparative analysis of various deterministic and probabilistic control scenarios that are based on occupant behavior. The study evaluates the effectiveness and validity of these proposed control scenarios, providing valuable insights for design decision-making.

This paper aims to establish a reliable scale measuring occupants’ levels of environmental trust in their work settings’ indoor air quality and explore the relationship between occupants’ levels of environmental trust and their perceived control over the air quality in their workspace.

The authors conducted occupant surveys concerning indoor air quality in an office building, and collected corresponding indoor air quality measurements. Descriptive statistics and correlation analysis results are reported to reveal occupants’ levels of environmental trust and perceived control.

Results reveal that psychological perceptions of indoor air quality can be quite neutral, even shortly after an extreme wildfire event resulting in very poor air quality in an urban area. Occupants’ sense of trust that their office building could protect them from harmful air outside, and their belief that the building could protect them from seasonal smoky conditions, each correlated positively with employees’ sense of control over the indoor air quality in their personal workspace.

This case study adds to an interdisciplinary understanding for facility managers and organizational leaders concerning a way to measure occupants’ sense of control over the indoor air quality in their building, as well as their environmental trust in terms of how protected they feel from harmful air quality conditions.

The sharing economy enables apartment owners to generate income from their assets. “Agoda Homes” is an online travel agent (OTA) that directly competes with Airbnb. A destination has to discover its competitiveness, but few studies have provided an overview of accommodation attributes in each destination, which are crucial to shaping its brand image. This paper aims to illustrate firm-generated content or attributes that apartment owners list about their properties on an OTA platform to comprehend factual information about apartments in each destination with various star ratings and user ratings and to formulate a research model for future studies.

Informational content and accommodation attributes for apartments are automatically collected using a Web scraping tool (the Data Miner). Descriptive statistics and text analysis (word cloud and word frequency) are used to analyze data.

Findings reveal the primary location, facilities, cleanliness and safety attributes for all apartments in each destination, along with star ratings and user ratings. A research framework for scholars is also suggested. Guidelines for stakeholders in the tourism industry are additionally furnished.

This work concentrates on apartments, which have received less attention in the tourism literature. The study gathers factual data from a website to mitigate respondent bias issues inherent in the traditional survey methods.

While previous studies have highlighted the importance of incorporating environmental sustainability in building designs, there is a paucity of studies that assess the extent to which design teams in developing countries consider environmental sustainability at the building design stage. Therefore, using Zambia as a case study, this study examined the extent to which infrastructure design teams in a developing country consider environmental sustainability at the design stage.

The study used a qualitative research approach using structured interviews because there are hardly any studies which have explored the extent to which designers incorporate environmental sustainability in infrastructure designs in developing countries. The data is analysed thematically using the ATLAS.ti software.

The results show that environmental sustainability is not an important design consideration because it is secondary to functional, technical and aesthetic considerations. Environmental considerations are also made in an ad hoc manner and when it is cost-effective for the project. Regulatory requirements pertaining to environmental protection are adhered to without any cost considerations. It was, therefore, theorised that building design teams in developing countries make technical, functional and aesthetic consideration during the infrastructure design stage ahead of environmental considerations.

There is a paucity of studies that have investigated whether building infrastructure designers consider issues of environmental sustainability at the design stage in developing countries. The findings have practical implications on how developing countries can foster environmental sustainability at the design stage and avoid generating a building infrastructure stock that will require environmental resilience adaptation in the future.

The purpose of this paper is to systematically map research on the effect of classroom acoustics and noise on high school students’ listening, learning and well-being, as well as identify knowledge gaps to inform future research.

This scoping review followed the PRISMA-ScR protocol. A comprehensive search of four online databases (ERIC, PubMed, Scopus and Web of Science) was conducted. Peer-reviewed papers were included if they conducted a study on the effect of classroom acoustics or noise on students’ listening, learning or well-being; had a clear definition of the noise level measurement; were conducted with high school students; and had the full text in English available.

In total, 14 papers met the criteria to be included in the review. The majority of studies assessed the impact of noise on students’ listening, learning or well-being. Overall, the results showed that higher noise levels have a negative effect on students’ listening, learning and well-being. Effects were even more pronounced for students who were non-native speakers or those with special educational needs such as hearing loss. Therefore, it would be beneficial to limit unnecessary noise in the classroom as much as possible through acoustic insulation, acoustic treatment and classroom management strategies.

This paper is the first review paper to synthesize previous research on the effect of classroom acoustics and noise on high school students’ listening, learning and well-being. It provides an analysis of the limitations of existing literature and proposes future research to help fill in these gaps.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.