Exploring the Benefits of Mass Timber Construction in the Workplace: A Novel Primer for Research

Abstract

Mass timber construction has recently gained popularity due to its outstanding environmental benefits and building performance, which hold revolutionary potential for the construction industry. However, its impacts from the perspective of occupants have not been thoroughly explored. This study introduces an innovative empirical approach that explores the potential benefits of mass timber construction for individuals and organizations, with an emphasis on the workplace. We review the conceptual framework regarding how visual and physical exposure to timber construction materials and finishes have a positive effect on individuals and organizations at a broad level. We propose a more holistic mixed-method behavioral approach to studying occupant behavior and well-being by integrating self-reported questionnaires, objective biomarkers (heart rate variability and hair cortisol), and indoor environmental quality (IEQ) measures. Our study offers a novel research primer on the exploration of mass timber construction impacts and benefits for both office workers and construction workers. Participants from different office settings completed pre- and post-occupancy evaluation surveys to assess their experiences, including IEQ satisfaction, productivity, and health. Office workers were located in three different offices: a controlled laboratory environment, an open-plan office, and an open-plan space with a timber interior. The construction workers worked in a timber space for three months and then moved to work in a building with a concrete structure. The analysis included descriptive statistics, t-tests, ANOVA, and linear regression to compare differences between office settings and assess the relationship between environmental variables and overall satisfaction in IEQ, comfort, productivity, and health. In office workers, in terms of building image, thermal comfort, and artificial lighting, the data analysis revealed significant differences in occupants’ satisfaction levels between office settings. However, the low number of participants affected the results, and some factors were not found significant in relation to the office setting. Among tradespeople, there was no relationship between the building environment and productivity, health, or comfort. However, the results of hair cortisol testing indicated that working in a timber space can decrease the level of cortisol (stress) and have an impact on the productivity of workers. Such occupant’s perspective research is pivotal to informing policy makers, developers, business owners, construction professionals, timber industry stakeholders, environmentalists, and researchers in their decision-making processes. Fostering the future widespread adoption and advancement of mass timber construction.

1. Introduction

Mass timber construction (MTC) has recently gained notable popularity for two pivotal reasons. Firstly, owing to its substantial environmental benefits and the growing recognition of its commendable building performance [1,2]. And secondly, for the multifaceted advantages it offers to individuals and organizations. Such advantages include the positive impacts on wellness, efficiency, and productivity externalities [3,4].

Climate change stands as one of the most urgent challenges facing humanity on a global scale [5]. Rapid population growth and expanding urbanization are inflicting serious and devastating impacts on ecosystems. The construction industry is widely recognized as a primary contributor to environmental degradation in numerous countries [6,7,8]. It accounts for approximately 39% of the world’s carbon emissions, with 28% and 11% attributed to building operations and materials, respectively [9]. However, studies consistently demonstrate that the choice of materials wields a more significant influence on the life-cycle emissions of buildings compared to their operational phase [10,11]. In contemporary construction practices, concrete and steel materials, with their energy-intensive production processes, dominate. Yan et al. [8] have reported that roughly 82–87% of the total emissions tied to building operations stem from implicit emissions inherent in construction materials, and a substantial 94–95% of these emissions are linked to the use of concrete and steel. Acknowledging their substantial environmental impact, many countries and organizations are advocating for a revolution in green building practices (Green building is a trending method of construction that refers to the practice of siting, designing, construction, operation, maintenance, renovation, and demolition in an environmentally responsible and resource-efficient manner [12,13]. The goal of green building is to minimize the negative impacts of the built environment while creating healthy, energy-efficient, and comfortable spaces for people to live and work in.) A pivotal facet of this movement involves the careful selection of sustainable materials to replace concrete and steel, serving as a crucial strategy to mitigate construction-related emissions (e.g., [12,14,15]).

Considering the negative environmental impact of conventional building materials like steel and concrete, bio-based materials are increasingly gaining ground in the global construction sector [1,14]. Bio-based materials are defined as products derived and produced from biomass, such as plants, animals, or fungi, with a relatively short cycle time [16]. Common bio-based building materials include wood, hemp, rice hulls, bamboo, and composites derived from algae and mycelium. They are often linked to the term ‘circular economy’ and have advantages in reducing carbon footprints and improving energy efficiency [17]. Wood, a prime example of a bio-based building material, holds a prominent position due to its historical utilization dating back to early human civilizations [6]. However, it was historically restricted to small structures due to considerations of its structural properties, public perception, and government regulations since the first industrial revolution [18]. This period witnessed rapid industrialization, which led to the dominance of steel and concrete in architectural and engineering design. Despite this, recent advancements in gluing, fixing, fabrication, and fire suppression techniques have showcased that wood can indeed be a high-performance, sustainable building material, even for larger or taller structures when employed appropriately [4,15,19].

Considering this trend, across recent decades, MTC (the utilization of engineered timber products, e.g., massive wood planar or frame elements) as primary materials for core building elements has witnessed increasing adoption [2,19]. It has gained widespread recognition as the only renewable construction method capable not only of reducing emissions but also of generating negative emissions through carbon sequestration [4,10]. While a substantial body of research delves into the benefits and challenges of the MTC system from multiple perspectives, including material performance, economics, environment, and sustainability, limited investigation has centered on its impact from a stakeholder standpoint [1,7,19]. The risk-averse nature of the construction industry underscores the importance of a comprehensive grasp of the performance and benefits of novel and innovative construction techniques, such as MTC, across various dimensions [7,15]. Factors that have an impact on stakeholders are tied to softer value drivers, particularly the enhanced design quality outcomes achievable through MTC. These outcomes hold the potential to not only benefit end-users in terms of improved health, well-being, and productivity but also contribute to market advantages (such as financial returns and environmental, social, and governance investments) for building developers and asset managers [3,4,6].

Another important aspect of MTC that is not widely discussed in the literature is its human and organizational benefits [1]. Existing evidence has shown that MTC can create a comfortable indoor environment through its specific building attributes, including ventilation and air quality, thermal comfort, acoustics, and lighting (e.g., [20,21]). Moreover, according to the biophilic hypothesis, humans tend to seek a connection with nature, which triggers a positive attitude towards wood as a natural, warm, and healthy material [22,23]. For example, Nyrud and Bringslimark [24] reviewed studies investigating psychological responses to wood and confirmed the similarity of preferences for wood, with people favoring it because it is natural. Moreover, the affective response to wood appears to be measurable, giving indications of physiologically beneficial effects. Some studies have found that participants in environments with visual wood surfaces tend to show lower sympathetic nervous system activation, fear responses, and chronic stress (e.g., [21,25,26,27]. Furthermore, several scholars have found that exposure to wood in indoor environments can be associated with reduced stress and increased levels of well-being in subjects from different countries and scenarios, such as office environments, schools, and hospitals (e.g., [3,20,24,25]). However, most existing studies to date have been limited by cross-sectional designs, small (non-representative) samples, single indicators, self-reported data, and non-peer-reviewed publications. These limitations result in findings that are often at risk of bias and cannot be generalized, leaving a research gap for future studies.

Motivated by this existing research gap in the literature, this study provides a novel primer for research questions encompassing the human and organizational benefits of MTC, with a particular focus on its implications within the workplace. We do this by introducing an innovative, rigorous, and easily reproducible study design aimed at exploring the human and organizational benefits of MTC in an attempt to address previous limitations outlined in the literature. An in-depth comprehension of the impact of MTC on human and organizational performance has the potential to yield numerous benefits and implications from multiple perspectives—ranging from individual to organizational to societal. This understanding can guide design choices and construction practices to prioritize the well-being of building occupants while concurrently achieving mutually beneficial outcomes for individuals and organizations. More importantly, delving into such drivers of occupational wellness may also foster innovation and the evolution of novel building practices while informing policy decisions aimed at establishing an efficient and sustainable built environment.

2. Background

Across recent decades, well-being in the workplace has been receiving increasing attention and focus. Early literature in the field of organization and occupational health primarily focused on negative labor outcomes and attitudes, such as illness, work-related injuries, sick leave, and depression [28]. Researchers attempted to address the issue by mitigating or eliminating negative effects, which led to a negativist bias [29]. More recent organizational and positive psychology movements have instead emphasized the importance of employee health and well-being in the workplace (e.g., [29,30]). This is in line with the World Health Organization’s definition of health as ‘a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity’ [31]. Work well-being is related to different aspects of the workplace, such as the physical environment, relationships in the organization, the work climate, and the employees’ perceptions of their work [32]. At its core, it is about ensuring that employees are safe, healthy, and satisfied at work by reducing stress, injury, and pathogenic factors in the workplace through appropriate preventive and intervention measures within the organization [30]. An increasing number of organizations from different countries are developing relevant strategies for promoting employee well-being.

The emphasis on work well-being by organizations arguably stems from progressive recognition of the dual benefits to both the organization and the employee. The conventional theory is that organizational and employee well-being is a zero-sum game where if one party maximizes its utility, the other party will lose everything [33,34]. In this context, the previous view emphasized the development of effective organizational processes and structures to create mechanisms for maximizing critical outcomes (e.g., performance and production). The latest evidence, however, demonstrates that a win-win situation can be achieved for organizations and employees in terms of both economic aspects and well-being (e.g., [30,35]). There is a wealth of evidence that the overall health and well-being of the workforce have a positive impact on productivity. The happy-productive worker hypothesis, for instance, suggests that a higher level of employees’ subjective well-being and job satisfaction is positively associated with their job performance, productivity, and organizational citizenship and negatively associated with their absenteeism and turnover (e.g., [36,37]). Therefore, there is a clear benefit to organizations and related stakeholders clearly understanding the importance of integrating work well-being into organizational strategies and optimizing their interactions to achieve effective and sustainable organizational development [30].

There are various factors (both internal and external) that can influence well-being in the workplace, with increasing attention being paid to the role of the physical environment. The physical work environment is defined as encompassing all the material objects and stimuli that employees are exposed to in the workplace [38]. One of the newer topics is green buildings, where MTC is recognized as a part of green buildings. The World Green Building Council advocates that human resources account for approximately 90% of organizational expenditures, far outweighing building costs [39]. Therefore, a well-designed green building can have a significant impact on well-being in the workplace. The existing literature has found that green buildings can influence employee health, comfort, and well-being through different factors, such as indoor environmental quality (IEQ), temperature, lighting, color, and layout [13,40]. As a result, many Green Building Rating Tools, such as the Building Research Establishment Environmental Assessment Method (BREAM), the Comprehensive Assessment System for Built Environment Efficiency (CASBEE), and Leadership in Energy and Environmental Design (LEED), incorporate employee health, well-being, and IEQ into their systems. In turn, this aspect focuses on the quality of the building’s end-user experience, which is usually assessed through a post-occupancy evaluation [41,42].

The physical work environment has a profound impact on the physical and psychological well-being of employees. A poorly designed building can lead to the occurrence of sick building syndrome (SBS), which is a condition in which building occupants experience significant health or comfort-related effects, such as headaches, throat irritation, dry cough, itchy skin, fatigue, allergies, flu-like symptoms, and an increased incidence of asthma [43]. Since employees spend a considerable portion of their day in the office, the negative health effects of SBS can result in increased sick leave, absenteeism, reduced productivity, and even extend into their everyday lives outside of the workplace. Several studies have demonstrated that green buildings can promote employee health through improved comfort and IEQ. For instance, a longitudinal study conducted in the USA found a reduction in clinical symptoms and absenteeism among occupants who moved from a conventional building to a green building [44]. In addition, better IEQ provided by green buildings can improve employees’ sleep patterns, reduce physical symptoms, and decrease the occurrence of airborne infectious diseases by positively influencing thermal conditions, lighting, ventilation, and aesthetic appearance (e.g., [40,43]). Furthermore, a growing number of studies have found that green buildings are associated with improved employee well-being and productivity, resulting in significant financial returns for organizations (e.g., [13,45]). Even a minor improvement in employee performance can have a positive impact on an organization’s operations, suggesting that green buildings can provide a strong economic driver for organizations.

MTC, as a part of green buildings, has also been found to have a positive impact on human comfort, health, and well-being, which has been relatively underexplored in the literature [1]. It can create a comfortable interior environment through its specific building properties, including ventilation and air quality, thermal comfort, acoustics, and lighting (e.g., [20,40]). According to the biophilic hypothesis, humans tend to seek a connection with nature, which triggers a positive attitude towards wood as a natural, warm, and healthy material [23]. For example, Nyrud and Bringslimark [24] reviewed studies that investigated psychological responses to wood and confirmed preferences due to its natural characteristics. In addition, affective responses toward wood appear to be measurable, providing indications of beneficial psychological effects. Furthermore, several studies have found that environments with visual wood surfaces tend to lead to lower activation of the sympathetic nervous system, reduced fear responses, and decreased chronic stress among participants (e.g., [21,25,27]). Scholars have also observed that exposure to wood in indoor environments is associated with reduced stress and increased levels of well-being in various settings, including office environments, schools, and hospitals, across different countries (e.g., [3,20,25,40]). In short, albeit limited, there is literature examining the relationship between green buildings, particularly timber buildings, and workplace well-being.

However, most studies focus on the impact of a single workplace characteristic on a few health or well-being indicators rather than taking a more holistic approach. Moreover, there are considerable variations in the choice of health and well-being indicators and measures, as well as in the aspects of the physical environment studied. In addition, many studies are limited by cross-sectional study designs, which make it difficult to establish any causal relationships. The limited longitudinal studies conducted to date have focused on the broad concept of well-being without delving into its specific components. Furthermore, the existing studies have been conducted in specific contexts (e.g., country, sample selection, and scenario), and therefore, the results are not easily comparable or replicable in different contexts. Future research could extend current insights through a more comprehensive approach and careful selection of appropriate measures. This would help address the limitations of previous studies and provide a more nuanced understanding of the relationship between MTC and well-being. Additionally, conducting research in various contexts and settings would enable the generalizability and applicability of the findings, contributing to the development of evidence-based guidelines and practices for creating healthier and more supportive work environments.

2.1. Design—Sample Populations

2.1.1. Study 1—Office Workers and Students

For office workers and students, who often spend long hours in the office, the physical environment is critical to supporting their health, well-being, and performance. Much of the literature on the human benefits of timber building has focused on this particular group. For example, a recent study commissioned by Forest and Wood Products Australia surveyed 1000 indoor workers [46] and found that respondents who worked in environments featuring wood reported higher satisfaction, a stronger connection to nature, and a more positive experience of the workplace. They also reported increased productivity, better concentration, and an overall more positive mood. In general, studying office workers in timber construction is critical for understanding the impact of the built environment on their well-being, productivity, and satisfaction.

For students, it is widely recognized that creating an ideal physical learning environment plays an important role in promoting student well-being, learning experience, performance, and long-term personal development (e.g., [3,47,48]). As the use of wood in school construction and interior design is increasing, it is important to investigate whether timber buildings or wooden interiors can have positive impacts on student experience, such as well-being and productivity. Some studies have tentatively explored this question. For example, an Austrian study that tracked 52 students for one year found that students tended to experience less stress, as indicated by lower heart rates when completing competitions in a solid wood classroom [49]. Other studies have also found that students’ attempts to connect with nature, facilitated by the biophilic features of wooden buildings, can improve their academic performance [3]. Research may then explore how design elements of wood, such as its natural aesthetics and biophilic features, affect students’ cognitive function, attention span, mental health, and overall academic performance. In short, understanding these dynamics can inform future (primary, secondary, and tertiary) school design strategies that optimize learning environments and improve students’ performance and well-being.

2.1.2. Study 2—Construction Workers and Tradespeople

Construction workers often have demanding jobs that involve physical exertion, mental health challenges, complex tasks, and exposure to hazardous conditions [50,51]. Given such, a conducive physical work environment plays a crucial role in ensuring their well-being, productivity, and safety (e.g., [50,52,53]). Construction workers can be directly influenced by the increasing prevalence of mass wooden construction, and yet this is an area that has received limited exploration in the research literature. It is also interesting to explore whether MTC can mitigate safety hazards faced by construction workers through the reduction of noise and pollution associated with off-site manufacturing. Additionally, we are also interested in whether the biophilic feature of MTC can bring physiological and psychological benefits to construction workers. Overall, studying construction workers in timber construction is essential for gaining a comprehensive understanding of the challenges and opportunities associated with this method of construction. It enables researchers to address worker safety issues, enhance training and skill development, improve productivity and efficiency, improve worker satisfaction and retention, and provide valuable lessons for future research.

3. Materials and Methods

In this section, we present a novel research approach aimed at more comprehensively investigating the impact of MTC on human and organizational performance in the workplace. Specifically, we outline the research design, the indicators to be measured, the analysis process, and other specific considerations.

3.1. Design

3.1.1. Study 1—Office Workers and Students

We introduce a 24-h back-to-back data collection method. Specifically, we recruit participants and observe them for two consecutive days at the University of Melbourne, Melbourne Connect Building. On the first day, participants were asked to work or study within a controlled laboratory environment (Sustainable and Healthy Environments—SHE Lab) for a period of time while researchers recorded their experiences as a baseline. On the second day, representing the follow-up, participants are randomly assigned to either continue working within the laboratory setting or move to an MTC area for work or study. In addition, we also consider assigning a group of participants to selected environments with wood interiors to differentiate the effects of visual exposure to wood on participants’ well-being.

There are two major advantages to this approach. First, the back-to-back method enabled researchers to gather data from participants in a relatively short period of time. This efficient approach allowed for a larger sample size and facilitated the collection of comprehensive data from various individuals. Second, compared to traditional longitudinal studies that require prolonged follow-up periods, this approach significantly reduces the burden on both participants and researchers. Participants are not required to commit to extended study periods, which can contribute to higher compliance rates and lower attrition rates.

However, despite the efficiency of back-to-back data collection methods, it poses a limitation in assessing the long-term effects of MTC on human well-being. Changes in well-being might manifest over a longer period of time, and the approach, which focuses more on the immediate impact of exposure to MTC, may not capture its cumulative impact on well-being. Furthermore, the transition of participants from the laboratory setting to an MTC introduces certain noise, potentially confounding the assessment of the unique impact of MTC.

It is worth noting that our proposed study design (to some extent) addresses methodological gaps in the existing literature on the human and organizational benefits of wooden buildings or interiors. Building upon previous small-scale randomized controlled trial studies in the literature, we present a more universal controlled trial where participants are randomly assigned to either the original lab control setting or one of two other construction types: one for MTC (primary treatment group) and one for non-MTC construction (second treatment group). This method also allows for the control of systematic differences between the groups using appropriate statistical methods to minimize sources of potential bias. Third, we collect a diverse set of variables using different methods (e.g., quantitative and qualitative), which provide a more comprehensive understanding of the human and organizational benefits of MTC as well as the underlying mechanisms. Lastly, this study’s design facilitates the execution of experiments among different populations or at various sites. This is a significant methodological aspect of scientific research that contributes to the validity, generalizability, and robustness of any potential findings.

3.1.2. Study 2—Construction Workers and Tradespeople

The tradesmen worked in a timber space at the first point of data collection and then were again sampled three months later when working in a building with a concrete structure. The same participants were recruited in both the timber space and the concrete space.

There are two main advantages to this study method, including the potential for comprehensive assessment and longitudinal monitoring. By combining subjective self-reports with biological measurements, the data collection method offers a comprehensive assessment of participants’ experiences and outcomes. This holistic approach enables researchers to collect both qualitative insights and quantitative data, providing a cohesive understanding of the impacts of the mass timber working environment on health, well-being, and productivity. Objective measurements allow for real-time monitoring of participants’ physiological changes stemming from their working environments. This provides immediate feedback and facilitates the identification of potential trends or patterns as they emerge.

Potential limitations of the study method may include the generalizability of findings to other populations or construction contexts. The duration of the intervention period (three months) may limit the ability to observe long-term effects. In addition, external factors, such as changes in work conditions or personal circumstances, may confound the results.

3.2. Measures

The careful selection of appropriate measures is crucial, as it ensures a more comprehensive evaluation of the practical impacts of MTC. We propose four key measurement clusters: a self-reported questionnaire, two biological measures of heart rate variability (HRV) and hair cortisol, and IEQ measures.

3.2.1. Self-Reported Questionnaire

To assess the human and organizational benefits of MTC, we developed a comprehensive survey tool that builds upon a collection of previously validated measures. The survey consisted of four sections. In the first section, we ask participants to provide some basic personal information, primarily demographic and socioeconomic indicators. The second section probed participants’ attitudes and preferences regarding building design. This included information about the building they were in, their feelings about the building environment, and a series of questions concerning potential symptoms of SBS [54]. In the third section, we asked participants about their work experience and health status (e.g., physical and mental health). We also inquired about their health-related behaviors, such as physical activity, sleep, smoking, and alcohol consumption. The multi-disciplinary survey approach reflects similar previous behavioral economics survey designs and methods [55,56,57,58].

We have designed a four-section survey aimed at collecting a comprehensive range of information from participants. All questions used in the survey are validated measures that have been widely adopted in economic, well-being, and construction research.

3.2.2. Demographic and Socioeconomic Information

Participants were asked about their basic demographic and socioeconomic background. This included gathering their demographic information, such as date of birth, gender, postcode of residence, and background. Then, the questionnaire delved into their socioeconomic status, including occupation, income, and educational attainment.

3.2.3. Attitudes and Preferences in Building Design

Participants were asked about their attitudes and preferences towards building design using existing questionnaires widely used in the field of construction. The main questionnaires utilized for this study were the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Standard 55 (ASHRAE, 2013) and the SBS questionnaires [54]. The questions included, but were not limited to, the basic characteristics of the building they were currently in, their perceptions of the building environment, their level of comfort, and questions about SBS, as well as their building-related health and productivity measures.

3.2.4. Life Experience and Health Status

Participants were asked questions related to their well-being at work, specifically regarding their life experiences and health status. The relevant questions used in this study were drawn from the National Institute for Occupational Safety and Health Worker Well-Being Questionnaire (NIOSH WellBQ) [59]. These questions focused on various aspects, including life satisfaction, work evaluation and experience, self-reported health (e.g., physical and mental health), and health-related behaviors (e.g., physical activity, sleep, smoking, and alcohol consumption).

3.3. HRV

There is growing interest in heart rate variability (HRV) across many disciplines, used as an indicator of acute and chronic stress, autonomic system dysfunction, mental ill health (such as anxiety and depression), and cognitive function. HRV explores the variation in time intervals between heartbeats (R-R intervals), typically measured non-invasively through methods like electrocardiography (ECG) [60,61]. It offers insights into autonomic heart regulation, revealing the interplay between parasympathetic (decreases heart rate) and sympathetic (increases heart rate) inputs, resulting in complex heart rate variability [62,63]. Chronically low HRV levels are linked to increased cardiovascular disease and mortality risks [64]. Given the autonomic nervous system’s regulation of heart rate, HRV also correlates with cognitive function, with higher HRV associated with better performance in attention and memory tasks [65].

Participants were fitted with a Polar H10 ECG chest strap (Polar Electro Oy, Kempele, Finland) and a Polar Unite (Polar Electro Oy, Kempele, Finland) watch following entry to the testing space on the first day. The chest strap was positioned inferior to the pectoralis muscle, in line with the participant’s sternum. As the ECG sensors require consistent skin contact, the chest strap was securely fitted to the torso. Participant comfort was checked, and adjustments were made as necessary. The watch was then fitted to the participant’s left wrist. The ECG signal from the chest strap was transmitted to the watch, allowing the researchers and participants to visualize a live feed from the chest wrap, reported as heart rate. Participants were instructed to avoid submersion in water and to keep both the watch and chest strap secured until their return to the testing space on the following day. Unfortunately, due to researcher error, a significant amount of data was not recorded correctly and/or lost. As such, our study provides an analysis of only a small amount of the data originally attempted to be collected.

3.4. Hair Cortisol

Cortisol, often referred to as the stress hormone, plays a key role in the human body as a response to stress [66]. Conventionally, cortisol has been measured through saliva, blood, or urine samples, furnishing insights into short-term stress levels. The analysis of hair cortisol has recently emerged as an innovative technique for gauging chronic stress levels, providing distinctive perspectives on the prolonged functionality of the hypothalamic-pituitary-adrenal axis [67]. Hair cortisol levels reflect the cortisol integrated within the growing hair shafts. This cortisol infiltrates the hair follicles via capillaries and accumulates in the hair over time. Given that hair grows at an average monthly rate of 1 cm, a hair strand can offer stress-related information over multiple months [66,68]. Hair samples are collected close to the scalp, thus ensuring the sample captures as much recent cortisol exposure as possible.

Hair cortisol offers several advantages as a measure of stress and cortisol levels compared to other cortisol assessment methods. Firstly, it provides an assessment of cortisol levels over an extended period, typically ranging from weeks to months. This capability allows for the capture of chronic or cumulative cortisol exposure, making it a valuable tool for evaluating long-term stress levels (e.g., [66,67]). Secondly, the collection of hair samples for cortisol analysis is non-invasive and relatively simple. The procedure involves cutting a small amount of hair close to the scalp, which does not induce pain or discomfort. Consequently, it offers greater convenience and acceptability for participants in comparison to other methods that may necessitate blood draws or saliva samples. And finally, cortisol present in hair exhibits relatively stable properties and can be stored at room temperature for extended periods without degradation [69]. This allows for easy transportation and storage of samples, minimizing the need for specialized equipment or immediate processing. However, it is important to note that hair cortisol has its limitation controls during the analysis phase (e.g., [67,68]).

3.5. IEQ Measurement

This research measured a spectrum of variables to evaluate the thermal, air, lighting, and acoustic dimensions of Indoor Environmental Quality (IEQ) as illustrated in Figure 1. For thermal conditions, essential parameters such as air temperature, relative humidity, and air velocity were recorded to estimate the Predicted Mean Vote (PMV)—a widely recognized metric for assessing thermal comfort in mechanically ventilated buildings, as outlined in ANSI/ASHRAE Standard 55 [70]. Air quality was evaluated by measuring concentrations of carbon dioxide, particulate matter, and volatile organic compounds (VOCs). It is worth mentioning that the VOC assessment in this study focused on the detailed analysis of two terpenes associated with timber aroma (α-pinene and Limonene), as well as seven specific VOCs related to timber coatings (Formaldehyde, Benzene, Toluene, Ethyl Benzene, M-Xylene, P-Xylene, and Naphthalene). Lighting conditions were quantified by measuring illuminance level, Correlated Color Temperature (CCT), and Color Rendering Index (CRI). Acoustic quality was determined through measurements of sound levels in decibels (dB-A).

Continuous measurements of all the aforementioned variables were conducted across all three experimental sites for Study 1 at one-minute intervals. In contrast, logistical constraints hindered the setup of monitoring stations at the experimental sites for Study 2. Consequently, the assessment of Indoor Environmental Quality (IEQ) in Study 2 was primarily based on participants’ responses to questionnaires that explored their perceptions of the building environment and potential symptoms of Sick Building Syndrome, as detailed in the Section 3.2.1.

3.6. Ethics

This program of research was conducted in accordance with the 2023 Queensland University of Technology Ethics Committee approval number #6765.

3.7. Data Collection

3.7.1. Study 1—Data Capture

The study on office workers and students was conducted across three office settings: (1) a controlled laboratory environment (Lab); (2) Super Floor (an open-plan space with timber interior on a Mezzanine Level), and (3) Level 1 office (an open-plan office). A total of n = 27 participants took part in the study, with at least six participants assigned to each office setting. For the controlled measurement, all participants were located in the lab setting. The second round included the lab, Super Floor, and level 1. The groups and their study areas are presented in Figure 2.

3.7.2. Study 2—Data Capture

This study was a repeated experimental design consisting of two rounds. We recruited participants who had been working at the selected mass timber construction site to participate in the baseline data collection and then follow up after three months in the concrete building setting. In each round, participants were asked to complete a self-reported questionnaire and provide a small hair sample for cortisol analysis. The research participants were reimbursed an out-of-pocket payment of $50 at the end of each round to compensate for their time.

The mass timber construction site selected for this study was T3 Collingwood, located at 36 Wellington Street, Collingwood, Victoria, Australia (see Figure 3a,b). T3 Collingwood is one of Australia’s largest multi-storey buildings, with 10 of its 15 storeys constructed entirely of timber, featuring an exposed glulam post and beam structure with cross-laminated timber floor panels. We conducted the baseline study at T3 Collingwood on 25 August 2023, when construction was nearing completion. Ten construction workers who had been working on-site were recruited to participate in this study. On that day, we also used smart sensing technologies to monitor relevant environmental parameters at the site. These n = 11 participants were followed up at different locations in Melbourne in early November of the same year. Due to geographical, time, and financial constraints of the research project, several of the 1st round participants (n = 6) were working in other Australian states and territories and could not be located or did not wish to participate in the November second round follow-up study.

4. Results

4.1. Study 1

4.1.1. Study 1—HRV Analysis

The R-R interval data, representing the duration (in milliseconds) between successive R-waves of cardiac cycles, were initially captured using the Polar H10 chest strap. Subsequently, the data were exported as.csv files for detailed scrutiny in Microsoft 365 Excel (version 2310). Visual inspection aimed to identify any outliers, irregularities, or inaccuracies arising from placement issues with the Polar H10 chest strap. The exported data underwent reformatting to include an ascending time column (hr:min:sec) based on the R-R interval durations. To ensure accuracy, data points outside the designated baseline and exposure collection times were excluded. The refined dataset was then imported into Kubios HRV Standard version 3.5.0 for analysis. Kubios software facilitated the computation of key HRV parameters, including mean heart rate (HR), mean R-R intervals (RR), a standard deviation of NN intervals (SDNN), root mean square of successive differences (RMSSD), percentage of successive RR intervals differing by more than 50 ms (pNN50), high frequency (HF), and the ratio between low frequency and high-frequency power (LF/HF). These parameters, acknowledged as robust indicators of vagal tone [60], were computed based on established HRV analysis techniques.

4.1.2. Study 1—HRV Analysis

Four participants had complete data for HRV analysis. Results for mean RR, SDNN, RMSDD, pNN50, HF, and LF/HF in the SHE Lab and Mass Timber Construction for baseline and exposure for participants are displayed in

Table 1. Individual characteristics of heart rate variability indices and measures in baseline and exposure.

ID	Exposure	Baseline								Exposure
		Mean HR	HR SD	Mean RR	SDNN	RMSDD	pNN50	HF	LF/HF	Mean HR	HR SD	Mean RR	SDNN	RMSDD	pNN50	HF	LF/HF
1	Lab	84.1	3.8	713.36	31.926	24.246	3.6287	287.75	2.182	87.5	3.7	685.73	28.579	20.78	2.0297	269.27	1.785
2	Lab	84.6	4.1	709.1	34.189	22.741	3.0742	199.24	3.8174	70.5	3.1	851.15	37.398	34.211	12.633	504.38	1.5582
3	MTC	87.3	2.8	687.23	21.511	15.33	1.7182	118.29	1.9958	90.2	2.4	664.95	17.503	8.25	0.083	31.074	5.5558
4	MTC	83.2	3.9	721.21	32.025	32.455	9.6579	251.91	1.7456	89.8	5.5	667.9	39.493	35.947	5.7127	549.84	1.5012

Note: Lab = SHE Lab; MTC = Mass Timber Construction; HR = heart rate; HR SD = standard deviation of mean heart rate; RR = duration of an interval of successive R-waves; SDNN = standard deviation of NN intervals; RMSDD = root mean square of successive differences; pNN50 = percentage of successive RR intervals differing by more than 50 ms; HF = high frequency; LF/HF = ration between low frequency and high-frequency power.

, and graphically for each HRV domain in Figure 4. Due to problems surrounding HRV data collection, only 4 participants presented complete data for both baseline and exposure. Therefore, the interpretation of the HRV results must be approached with caution. The small sample size severely limits the statistical power and generalizability of the findings. Consequently, the HRV results should be considered exploratory and preliminary in nature. Further research with a larger and more representative sample is necessary to elucidate the potential relationship between the HRV variables and environmental exposure.

4.1.3. Study 1—IEQ Results

Table 2. Comparison of statistical metrics for IEQ measures.

	SHE Lab		Super Floor		MTC Space
IEQ Measures	Mean (SD)	Median (IQR)	Mean (SD)	Median (IQR)	Mean (SD)	Median (IQR)
Thermal
Temperature (°C)	21.86 (0.72)	21.60 (21.28, 22.41)	21.51 (0.72)	21.62 (20.95, 22.13)	22.44 (0.16)	22.49 (22.32, 22.55)
Relative Humidity (%)	38.73 (3.32)	39.71 (36.53, 40.68)	38.54 (1.90)	38.32 (37.34, 39.93)	34.94 (1.88)	35.14 (33.06, 36.51)
Air speed (m/s)	0.00 (0.01)	0.00 (0.00, 0.00)	Below LOD *	Below LOD *	0.01 (0.03)	0.00 (0.00, 0.00)
Predicted Mean Vote	−0.65 (0.20)	−0.74 (−0.81, −0.49)	−0.75 (0.19)	−0.72 (−0.90, −0.59)	−0.52 (0.04)	−0.51 (−0.55, −0.50)
Air
CO2 (ppm)	641.59 (161.90)	584.75 (541.00, 682.12)	509.34 (24.09)	503.00 (490.00, 532.00)	579.75 (28.48)	582.08 (562.62, 601.58)
PM2.5 (µg/m3)	1.90 (0.96)	1.83 (1.00, 2.33)	1.86 (1.02)	1.67 (1.00, 2.33)	2.08 (1.09)	2.00 (1.33, 2.50)
PM10 (µg/m3)	3.02 (1.80)	2.67 (2.00, 4.00)	3.04 (1.86)	2.67 (2.00, 4.00)	3.52 (2.00)	3.00 (2.00, 4.00)
Formaldehyde (ppm)	0.19 (0.03)	0.18 (0.17, 0.21)	0.11 (0.04)	0.09 (0.08, 0.12)	0.10 (0.02)	0.11 (0.07, 0.12)
Toluene (ppm)	0.00 (0.00)	0.00 (0.00, 0.00)	0.32 (0.16)	0.29 (0.21, 0.39)	0.01 (0.01)	0.00 (0.00, 0.00)
α-pinene Limonene Benzene Ethyl benzene M-Xylene P-Xylene Naphthalene (all in ppm)	Below LOD *	Below LOD *	Below LOD *	Below LOD *	Below LOD *	Below LOD *
Lighting
Light Intensity (Lux)	493.46 (52.38)	513.97 (449.37, 531.93)	768.89 (134.80)	752.60 (649.68, 864.96)	923.26 (129.45)	878.12 (817.15, 1035.50)
CCT (K)	4168.02 (36.13)	4183.00 (4140.00, 4198.00)	4283.48 (204.45)	4337.50 (4098.75, 4467.50)	6121.02 (89.84)	6161.00 (6027.75, 6202.00)
CRI (-)	86.57 (0.76)	86.96 (85.81, 87.24)	94.48 (0.31)	94.55 (94.29, 94.69)	92.35 (0.24)	92.45 (92.18, 92.53)
Acoustic
Sound Level (dB-A)	42.48 (6.91)	40.10 (38.30, 45.10)	45.32 (5.66)	43.70 (41.40, 47.50)	41.65 (5.09)	40.35 (38.12, 43.50)

* LOD: limit of detection.

provides a summary of the statistical metrics for IEQ measurements across all three experimental conditions. For the thermal comfort assessment, the Predicted Mean Votes (PMVs) of participants were calculated using the “pythermalcomfort” Python library package (version 2.6.0), which utilizes recorded data on air temperature, relative humidity, and air speed. These calculations were based on specific assumed conditions: a metabolic rate (MET) of 1.2 met, representative of seated reading tasks, and a clothing insulation (CLO) value of 0.61 clo, appropriate for participants wearing trousers and long-sleeve shirts [71]. The PMV results suggest that the thermal conditions at the three experimental sites are comparable, ranging from slightly cool to comfortable (−1 < PMV < 0).

The air quality across the three experimental sites showed notable differences. Specifically, CO₂ concentrations at the SHE Lab averaged around 640 ppm, significantly higher than those observed at the other two sites (p < 0.001); meanwhile, elevated levels of PM_2.5 and PM₁₀ were recorded at the MTC Space. Concentrations of VOCs associated with timber aroma and coating chemicals were generally below the detection limit, except for a discernible presence of formaldehyde at all three sites and toluene in the Super Floor space. The diversity in results for different air pollutants can be ascribed to a variety of factors, such as the distinct layout of spaces, interior material use, occupancy and human behavior, and the ventilation systems of each experimental site.

Lighting quality also exhibited significant variation across the three sites. Specifically, measurements of illuminance levels at worktable height revealed that the MTC space achieved the highest value, followed by the Super Floor, and then the SHE Lab. However, it’s noteworthy that the illuminance values for all three locations fall within the recommended range for performing typical office tasks of medium to high difficulty, as outlined in AS/NZS 1680.2.4:1997. In terms of Correlated Color Temperature (CCT), the MTC space utilized cool white lighting, in contrast to the natural white lighting adopted at the other two sites. The lighting across all three sites demonstrated excellent color rendering capabilities, with the Super Floor and MTC spaces registering higher CRI values (CRI > 90) compared to the SHE Lab (CRI ~ 86).

In terms of acoustic conditions, the Super Floor space is slightly noisier compared to the SHE Lab and MTC space. However, all three spaces maintain satisfactory acoustic environments, with median noise levels ranging between 40 and 45 dB-A.

4.1.4. Study 1—Questionnaire

Descriptive statistics are reported for the overall comfort, productivity, and health of the participants in each office setting. T-tests were conducted to compare differences within each group (before and after) and between groups (different office settings). Additionally, ANOVA tests were performed to compare differences between the groups that attended different office settings. Linear regression analysis was used to examine the relationship between various environmental variables (e.g., thermal comfort, visual noise) and overall satisfaction, productivity, and health.

To evaluate the overall comfort, productivity, and health of the participants in each setting (offices and construction sites), descriptive analysis was conducted. The basic information about these three office settings is summarized in

Table 3. Basic information of the respondents of student participants.

Information	Category	Count	N%
Birth year	1980–1990	7	26%
	1991–1995	10	37%
	1996–2000	7	26%
	2001–2005	3	11%
Gender	Male
	Female	12	44%
	Prefer not to say	15	56%
Type of employment	Full-time, permanent	14	52%
	Full-time, fixed-term contract	4	15%
	Part-time, permanent	0	0%
	Part-time, fixed-term contract	0	0%
	Part-time, causal	9	33%
Hours of work	<35	9	33%
	36–40	12	44%
	41–45	4	15%
	46–50	0	0%
	51–55	2	7%
Hours of work in office	<35	10	37%
	36–40	8	30%
	41–45	2	7%
	46–50	0	0%
	51–55	1	4%
Education	Below Year 12	0	0%
	Year 12	2	7%
	Diploma, Advanced Diploma, or Associate Degree	1	4%
	Bachelor’s degree (including Honors, and Graduate Diploma/Certificate)	9	33%
	Master’s Degree	15	56%
	Doctorate	0	0%
	Other, please specify _______________________	0	0%
	Prefer not to say	0	0%

.

Participants were 44% male and 56% female. As indicated in Table 3, participants had an average age of 28.93 years. Regarding their job and education attainment, 52% of participants were full-time (permanent), 4% of them were full-time with fixed-term contracts, and 9% were part-time (casual). In terms of hours of work, 44% of the participants worked between 36 and 40 h, 33% worked less than 35 h, and 15% worked between 41 and 45 h. Regarding hours of work in the office, 37% worked less than 35 h, 30% worked 36 to 40 h, and 11% of students worked more than 41 h.

4.1.5. Satisfaction with Office Settings and Its Impact on Productivity and Health

Descriptive analysis as shown in Figure 5 indicated that participants in Super Floor with timber indoor materials and outdoor views reported higher levels of overall comfort compared to the laboratory environment. The data revealed that 85% of the workers in the timber environment rated their overall comfort high, while this indicator was 43% for the workers in the laboratory environment. Specifically, participants on the Super Floor reported higher satisfaction with temperature, air, lighting, and overall comfort than the laboratory environment. Interestingly, 85% of the participants were satisfied with the temperature on the Super Floor, while only 34% of the participants rated the temperature of the laboratory as high.

In terms of the perception of participants, results also showed that the average satisfaction score with different aspects of IEQ and overall IEQ in the Super Floor and open-plan office was more than 5, indicating higher satisfaction with IEQ than with IEQ in the laboratory office.

Regarding the image of the building, the image of the indoor environment, and cleanliness, participants were asked to rate their physical environment by selecting options 1 to 7 (poor to good). As shown in Figure 6, 86% of the participants rated the image of the building on the Super Floor 6 out of 7, showing their higher satisfaction when compared to other settings.

When the participants were asked about the image of the indoor environment, all the participants showed higher satisfaction with the Super Floor, while 14% of participants were dissatisfied with this aspect in the laboratory and open-plan office. In terms of cleanliness, participants in all three office settings rated it as moderate to high (4 to 7). Participants were also asked about their perception of the amount of natural light in their office setting. While more than 70% of participants believed the natural light was little, no participants rated the natural light as little in the other office settings.

In terms of participants’ perceptions of the impact of the building on their health and productivity, Figure 7 indicates that participants were more satisfied in the Super Floor and open-plan office compared to the controlled laboratory environment. No participants on the Super Floor were unsatisfied about the impact of the building on their health in the Super Floor, while 10% and 14% of the participants in open-plan and laboratory settings indicated they felt less healthy, respectively. In terms of productivity, no participants rated their productivity low (−10% or less), while 14% of the participants in the laboratory environment rated it less productive. Moreover, 29% of participants on the Super Floor indicated that the impact of the building on their productivity was high (30% and more), while this indicator was 0 and 10% in the laboratory and open-plan office, respectively.

Regarding sources of discomfort, the percentage of participants with no discomfort was higher on the Super Floor (nearly 43%) than in the laboratory environment (nearly 29%). According to the participants, the hot/cold surfaces in the laboratory environment (29%) were nearly 2 times more than the Super Floor (14%). All the participants in the open-plan office complained about the noise of others, and 43% of them were also uncomfortable in terms of privacy (Figure 8).

To explore if there was any statistically significant difference between the perceptions of groups towards different aspects in different office settings, ANOVA tests were performed. Results showed significant differences in several aspects of IEQ between the laboratory environment and the other two settings of Super Floor and open-plan office. These aspects included overall comfort, artificial lights, air freshness, natural light, air satisfaction, feeling healthy in the building, and decor layout, which are shown in

Table 4. Comparison (ANOVA test results) between office settings.

Variable	Sum of Squares (SS)	Mean Square (MS)	p-Value
Building Image	3.05	1.52	Not significant
Overall comfort	16.59	8.30	0.01
Artificial lights	14.47	7.23	0.01
Thermal perception	1.90	0.95	Not significant
Temperature stability	8.54	4.27	Not significant
Air humidity	1.22	0.61	Not significant
Air freshness	24.35	12.17	0.00
Air smell	1.68	0.84	Not significant
Natural light	25.34	12.67	0.00
Glare from sun	5.22	2.61	Not significant
Glare from light	3.58	1.79	Not significant
Temperature satisfaction	7.76	3.88	Not significant
Air satisfaction	12.41	6.21	0.02
Overall lighting	5.37	2.68	Not significant
Noise satisfaction	8.19	4.10	Not significant
Overall comfort	2.75	1.38	Not significant
Noise inside	9.71	4.86	Not significant
Noise outside	1.79	0.89	Not significant
Health	12.93	6.46	0.00
Productivity	1.79	0.89	Not significant
Décor layout	7.45	3.72	0.05
Cleanliness	0.23	0.12	Not significant

Note: the mean value was significant at the 0.05 level.

.

To explore any differences between the satisfaction of different aspects mentioned in the descriptive analysis when participants worked in the laboratory on the first day and then on the Super Floor the following day, a series of t-tests were conducted.

Table 5. Comparison (dependent t-test results) between mean differences in office settings.

		Laboratory		Super Floor
Variable	Satisfaction with …	Mean	Std Dev.	Mean	Std Dev.	Mean Difference	Significance	Effect Size (Cohen’s D)
Image of building	How do you rate the image that the building as a whole present to visitors?	5.14	0.69	5.86	0.38	0.71	0.04	0.39
Temperature Comfort	How would you describe the temperature and air conditions in your work area over the past three months?	4.71	0.76	5.71	0.76	1.00	0.03	0.50
Temperature		4.83	2.27	6.00	2.34	1.17	Not significant	-
Air		5.14	1.21	6.14	0.69	1.00	Not significant	-
Air smell		3.00	1.15	2.57	1.27	−0.43	Not significant	-
Air quality		4.14	1.57	3.14	1.35	−1.00	Not significant	-
Artificial Light	How would you describe the quality of the lighting in your normal work area?	3.29	3.44	3.00	3.44	0.29	Not significant	-
Overall lighting		5.14	1.46	6.00	0.58	0.86	Not significant	-
Light Glare		3.43	1.81	2.14	1.46	−1.29	Not significant	-
Daylight glare		3.29	2.21	2.29	1.25	−1.00	Not significant	-
Daylight		4.57	1.27	4.86	0.90	0.29	Not significant	-
Outside noise	How would you describe noise in your normal work area?	3.29	1.80	2.14	1.07	−1.14	Not significant	-
Noise		5.29	1.11	4.29	1.98	−2.31	Not significant	-
Inside noise		3.29	1.11	3.86	1.21	0.57	Not significant	-
Image of Indoor Environment	How do you rate the image that the indoor environment (e.g., décor, layout) as a whole present to visitors?	5.29	0.49	5.71	0.49	0.43	Not significant	-
Cleanliness	How would you rate the cleanliness of your office?	5.57	0.79	6.00	1.00	0.43	Not significant	-
Health	Overall, do you feel less or more healthy when you are in the building?	4.86	1.07	5.43	0.53	0.57	Not significant	-
Overall Comfort	All things considered, are you satisfied with the overall comfort of the building?	5.29	1.11	6.00	0.58	0.71	Not significant	-
Productivity	Could you estimate how environmental conditions in the building have affected your productivity at work over the past three months?	5.43	1.51	5.57	1.13	0.14	Not significant	-

shows the means and standard deviations of the aspects related to the IEQ and the physical environment for the office settings. It also presents the comparison between the mean scores and their significance and effect sizes for participants when working in different settings.

The t-test results showed insignificant differences when comparing participants who worked in the laboratory for two consecutive days. In general, the satisfaction of the participants for the majority of factors was higher on the Super Floor (e.g., building image, IEQ, health, etc.) than in the controlled laboratory environment. However, not all the factors showed significant differences in terms of satisfaction when the perceptions of participants working in the Super Floor and laboratory environments were compared. The t-test results revealed that factors such as the image of the building and temperature were significant (p < 0.05) when the Super Floor and laboratory were compared.

No significant differences were observed between before and after surveys related to other aspects of IEQ, health, productivity, and satisfaction, possibly due to the limited number of participants and a lack of controlled variables in the study. Therefore, to clarify the difference between office settings, research with a much larger number of participants is recommended.

4.1.6. Drivers of Productivity, Feeling Healthy, and Overall Comfort

To explore how physical and IEQ aspects of the building (image of the building, image of the indoor environment, and cleanliness) impact feeling healthy, overall comfort, and productivity, separate multiple linear regressions were conducted. Comfort, productivity, and feeling healthy were considered dependent variables, with all other data aspects considered independent variables.

Table 6. Regression results with comfort, productivity, and health as dependent variables in different office settings.

Super Floor	Dependent Variable
Independent Variable	Overall Comfort			Feeling Healthy			Productivity
	R2	Coefficients	p-value	R2	Coefficients	p-value	R2	Coefficients	p-value
Noise	0.73	0.29	0.03	0.11	0.09	Not significant	0.99	0.83	0.00
Light	0.66	0.66	Not significant	0.29	−0.5	Not significant		2.06	0.00
Air	0.17	0.35	Not significant	0.70	0.70	0.02	0.01	−0.2	Not significant
Laboratory environment
Temperature	0.55	0.31	0.02	0.06	0.22	Not significant	0.15	0.37	Not significant
Cleanliness		0.38	Not significant	0.01	0.2	Not significant	0.35	−0.67	Not significant
Noise		0.26	0.05	0.06	−0.21	Not significant	0.00	−0.07	Not significant
Air		0.40	0.01	0.00	0.01	Not significant	0.06	0.26	Not significant
Image of the indoor environment	0.012	0.1	Not significant	0.03	0.20	Not significant	0.34	0.53	0.00
Artificial Light	0.42	0.47	0.00	0.07	0.20	Not significant		0.37	0.02
Open-plan office
Temperature	0.77	0.85	0.02	1	0.07	0.00	0.004	−0.01	Not significant
Artificial light	0.50	0.36	Not significant		0.27	0.00	0.039	0.08	Not significant
Air	0..02	0.07	Not significant		−0.06	0.00	0.33	0.22	Not significant
Cleanliness	0.25	−0.5	Not significant	0.02	0.18	Not significant	0.59	1.38	0.05
Image of the indoor environment	0.58	−0.82	Not significant	2.08	−2.92	Not significant		−1.48	0.10
Image of building	0.25	−0.5	Not significant	0.01	0.11	Not significant		0.88	0.08

summarizes the coefficients and R2 values for the regression results.

In the Super Floor, noise satisfaction was the predictor of productivity with coefficients of 0.83 (p < 0.01). For overall comfort, light satisfaction was the highest predictor with a coefficient of 2.06 (p < 0.01), while noise was the second predictor with a coefficient of 0.29 (p < 0.05).

For the laboratory environment, temperature, air, and noise affected workers’ overall comfort with air satisfaction and cleanliness as the strongest predictors with coefficients of 0.4 (p < 0.01) and 0.38 (p < 0.05), respectively. This was followed by temperature and noise as the third and fourth variables predicting the overall comfort with coefficients of 0.31 (p < 0.05) and 0.26 (p < 0.05), respectively. While feeling healthy was not dependent on any aspects of IEQ or physical environment, productivity was dependent on the image of the indoor environment and artificial light as predictive variables.

Participants’ overall comfort in the open-plan office was related to temperature satisfaction, while their feeling of health was correlated with the independent variables of temperature, artificial light, and air satisfaction individually. In terms of productivity, participants were impacted by cleanliness, the image of the indoor, and the image of the building as a group of independent variables in one regression specification.

4.2. Study 2

4.2.1. Study 2—Cortisol Analysis

In our repeated (3-month) measures sample (n = 5) we exclude observation “10” as an outlier due to an unexplainably/disproportionately high first sample observation = 2956.27.

For our other 4 observations, we see the Mean at t = 284.12 almost doubles to a mean at t + 1 = 549.04, and SD tightens from t = 117.33 to t + 1 = 78.60. Importantly our t-test shows statistical significance at a 5% with p = 0.037.

Our findings in

Table 7. Regression results with comfort, productivity, and health as dependent variables in different office settings.

Participant (Aug 2023)	Sample Weight (mg)	Cortisol (pg/mg)	Participant (Nov 2023)	Sample Weight (mg)	Cortisol (pg/mg)
13	5.3	234.494	13 (2)	5.6	521.871
10	5.3	2956.276	10 (2)	5.0	629.607
07	5.6	349.409	07 (2)	4.9	550.513
02	5.8	407.53	02 (2)	5.5	432.23
09	5.3	145.048	09 (2)	5.2	611.016

suggest that for all four of our participants of interest, after working in the mass timber construction setting (August 2023) and transferring to a concrete setting (Nov 2023) all four tradesperson’s cortisol (stress levels) increased.

4.2.2. Study 2—Questionnaire Analysis

As previously mentioned, our study sampled n = 11 participants at baseline who had been working in the selected mass timber building (T3 Collingwood). All 10 participants were male, with an average age of 31.40 years (SD = 5.38). Regarding their anthropometric measures, their average height was 178.70 cm (SD = 9.14), and their average weight was 83.90 kg (SD = 8.14). Regarding their job and education attainment, the 10 participants were full-time, permanent construction workers with an average of 45.90 (SD = 5.41) hours of work per week and an average of 8.07 (SD = 7.22) years of work experience. Among these 10 participants, 60% had a degree of Year 12 or less, 30% had a diploma degree, and 10% had a bachelor’s degree or above. Information about workers’ profiles is depicted in

Table 8. Basic information of the respondents of construction workers and tradespeople.

Information	Category	Count	N%
Birth year	1980–1990	2	33%
	1991–1995	3	50%
	1996–2000	1	17%
Gender	Male	6	100%
	Female	0	0%
	Prefer not to say	0	0%
Type of employment	Full-time, permanent	6	100%
	Full-time, fixed-term contract	0	0%
	Part-time, permanent	0	0%
	Part-time, fixed-term contract	0	0%
	Part-time, causal	0	0%
Hours of work	36–40	3	50%
	41–45	1	17%
	46–50	1	17%
	51–55	1	17%
Hours of work in office	36–40	3	50%
	41–45	1	17%
	46–50	1	17%
	51–55	1	17%
Education	Below Year 12	1	17%
	Year 12	2	33%
	Diploma, Advanced Diploma	2	33%
	Bachelor degree	1	17%
	Master’s Degree	0	0%
	Doctorate/PhD	0	0%

.

After approximately three months, 6 participants (60% of the baseline sample) participated in the follow-up study, and the remaining 5 participants were unable to participate in the second round of data capture as they were located in vastly different locations outside of Victoria, Australia (i.e., Sydney and Tasmania). Therefore, the 6 tradesmen who participated in both the baseline and follow-up were the sample of interest for our subsequent cortisol and survey analyses (one participant did not provide cortisol samples).

4.2.3. Satisfaction with the Building and its Impact on Productivity and Health

Descriptive analysis of the questionnaire indicated that participants were satisfied with the image of the building and the indoor environment (Figure 9). In these questions, respondents indicated their satisfaction with specific aspects of the physical environment by selecting options 1 to 7 (poor to good).

In terms of participants’ perceptions of the impact of the building on their health and productivity, results indicate that participants are more satisfied in the timber setting, with 33% rating it as high (7), while no participants rated poor health (1 and 2) in the timber setting. More than 80% of participants indicated that the impact of the building on their productivity in the timber setting is high (20% and more), while this indicator is 50% for the concrete setting (Figure 10).

When the participants were asked about the overall comfort of the building, more than 80% of them were highly satisfied (rated 6 and 7) in the timber environment, while half of the participants rated high (6 and 7) for the concrete setting (Figure 11).

To indicate if there is any difference between satisfaction of the different aspects mentioned in the descriptive analysis, a series of t-tests were conducted.

Table 9. Comparison (dependent t-test results) between mean differences in timber and concrete workplaces.

		Timber		Concrete
	Satisfaction with …	Mean	Std Dev.	Mean	Std Dev.	Mean Difference a	Significance
Image	How do you rate the image that the building as a whole present to visitors?	6.15	0.69	5.5	1.38	0.65	Not significant
Image of the indoor environment	How do you rate the image that the indoor environment (e.g., décor, layout) as a whole present to visitors?	6.16	0.89	5.16	1.67	1	Not significant
Feeling healthy	Overall, do you feel less or more healthy when you are in the building?	5.6	1.10	4.5	1.71	1.1	Not significant
Productivity	Could you estimate how environmental conditions in the building have affected your productivity at work over the past three months?	5.8	0.89	4.6	1.79	1.2	Not significant
Overall comfort	All things considered, are you satisfied with the overall comfort of the building environment?	6.16	0.69	5.5	1.38	0.66	Not significant

^a Mean differences were calculated by subtracting the mean satisfaction scores of timber and concrete workspaces.

shows the means and standard deviations of the aspects related to the physical environment for timber and concrete. It also presents the comparison between the mean scores and their significance and effect sizes for these two groups.

In general, the satisfaction of the participants in terms of all factors was higher in the timber setting. However, the t-test results did not indicate any significant difference between the two groups. These results may be impacted by the low number of participants. To clarify the difference between timber and concrete settings, more studies with a higher number of participants are recommended. The greatest differences (non-significance) in mean scores were seen in the impact of the building environment on productivity (mean difference = 1.2), feeling healthy in the building (mean difference = 1.1), and the image of the indoor environment (mean difference = 1). The smallest (non-significant) differences were seen in overall comfort and the image of the building, for which the timber setting showed very minor differences.

4.2.4. Drivers of Productivity, Feeling Healthy, and Overall Comfort

To indicate how physical aspects of the building (image and image of the indoor environment) had an impact on feeling healthy, overall comfort, and productivity, separate multiple linear regressions were conducted. Productivity and overall comfort and feeling healthy were considered as the dependent variables with the two physical factors (image and image of the indoor environment) as independent variables.

Table 10. Results of linear regression data analyses for each factor.

Independent Variables	Image of the Building			Image of the Indoor Environment
	R2	Coefficients	Significance	R2	Coefficients	Significance
Timber
Overall comfort	0.06	0.71	Not significant	0.07	0.59	Not significant
Feeling healthy	0.15	0.57	Not significant	0.05	0.27	Not significant
Productivity	0.01	−0.14	Not significant	0.03	−0.17	Not significant
Concrete
Overall comfort	0.62	0.8	Not significant	0.47	0.56	Not significant
Feeling healthy	0.32	0.7	Not significant	0.53	0.74	Not significant
Productivity	0.49	0.9	Not significant	0.72	0.91	Not significant

presents the results of linear regression. As presented in the table, no significant relationship between the variables was found, which could be the result of the low number of participants.

5. Discussion

MTC is one of the few structural products capable of challenging the dominance of mainstream reinforced concrete and steel design, which has been increasing [1]. Wood is the only renewable construction material that not only reduces emissions but also produces negative emissions through carbon sequestration (e.g., [4,10,11]). A growing number of governments have introduced policies to encourage the use of wood in building practice as part of the green building revolution (e.g., [6,72,73]). These policies demonstrate ambition to achieve sustainability goals for the construction sector, aligning with the Paris Agreement and the Net Zero Carbon Building Commitment [74,75]. And while there is already a well-established market for MTC in some European countries such as Austria, Denmark, Germany, Sweden, Switzerland, and the United Kingdom, it is still a nascent industry in other countries [3,19,76]. Given the risk-averse nature of the construction industry, the adoption of new and innovative materials like MTC requires a comprehensive understanding of their performance and benefits from various aspects [7,15]. While there is a large body of research exploring the benefits and challenges of MTC from different perspectives, such as material performance, economics, environment, and sustainability, only limited research has been conducted on its impacts from a stakeholder’s perspective [1,7]. The purpose of this project was to explore the human and organizational workplace benefits of MTC.

Through a review of the existing literature, we found that MTC has a positive impact on human comfort, health, and well-being. It can create a comfortable indoor environment through its specific building properties [20]. Moreover, according to the biophilic hypothesis, humans tend to seek a connection with nature, which triggers a positive attitude towards wood as a natural, warm, and healthy material (e.g., [21,25,27]). Furthermore, several studies have found that exposure to wood in indoor environments tends to be associated with reduced stress and increased levels of well-being and performance in various settings, such as office environments, schools, and hospitals, across different countries (e.g., [3,20,24,25]). These findings represent a softer value driver for the promotion of MTC from an end-user perspective. However, a large part of the existing literature is limited by study design, such as cross-sectional study designs, non-representative samples, and single measures.

One of the indicators that can be measured to assess the level of stress in occupants is cortisol. Our data, in line with previous research led by Yao et al. [77], Ríos-Rodríguez et al. [78], Lipovac and Burnard [27], and Burnard and Kutnar [79] has shown that exposure to natural elements, such as wood, decreases cortisol levels by promoting a sense of calm and relaxation, leading to stress reduction and health improvement. These studies indicated that there is a relationship between stress and productivity. Consistent with findings by Bain et al. [80], when investigating cortisol levels, our data showed that all workers exhibited higher cortisol levels in concrete buildings compared to timber structures.

In alignment with studies such as Kotradyova et al. [81], Pisaniello et al. [82], Fell [83], and Zhang et al. [84], our survey data also qualified the positive impact of exposure to a timber structure environment on feeling healthy, productivity, and comfort. Our Melbourne Connect study conducted in three design settings comparing timber, open-plan offices, and laboratory settings demonstrated that participants who worked on the Super Floor with more timber materials showed a higher level of satisfaction with temperature, air quality, lighting, and overall comfort than those in the laboratory environment, which is consistent with the findings by Zhang et al. [85]. The results indicated similar levels of satisfaction with the indoor environment and the overall building in the timber-rich environment compared to the other two settings, as suggested by Zhang et al. [85]. The satisfaction with health and perception of feeling healthy and comfortable found in our study and supported by others are key drivers for the choice of materials and the use of biophilic design, pointing to the important role that workplaces play in productivity.

However, it should be noted that our regression analysis could not find a significant result on how different aspects of the indoor environment impact productivity, health, and comfort. This was due to a lack of statistical power stemming from the small number of participants.

Similar to office workers, as suggested by Ojala et al. [86], tradespeople reported higher satisfaction with buildings when they worked in timber structures. The percentages also indicated higher satisfaction with aspects such as health, comfort, and productivity, in accordance with studies by Lee et al. [87]. However, our survey did not establish a significant relationship between the impact of the building on these aspects (health, comfort, and productivity).

Our research primer introduces a flexible and innovative methodology that researchers can adapt to their own building and construction research questions in subsequent studies. In addition, we incorporate two easily measurable biomarkers to complement the robustness of the self-report questionnaires that have been used alone in many existing studies. These biomarkers (HRV and hair cortisol) provide objective and standardized data about an individual’s health status, thereby yielding more accurate and meaningful results compared to self-reported data (e.g., [88,89]).

6. Conclusions

We propose a novel and more comprehensive approach to studying the human and organizational benefits of MTC in the workplace. A unique combination of self-reported questionnaires, objective biomarkers such as HRV and hair cortisol, and other relevant techniques (such as IEQ) can address some of the limitations of prior building and construction research.

Our study aligns with existing literature that revealed MTC’s contribution to lowering cortisol levels for trade workers as well as increasing satisfaction levels for office workers. The integration of timber as a biophilic design element is shown to reduce stress and enhance comfort, further emphasizing the potential of MTC to positively influence various aspects of the indoor environment. Moreover, our findings are in line with previous observations, indicating that tradespeople exhibit higher satisfaction and perceived health benefits when working in space with more timber materials. The results could suggest potential enhancements in productivity and overall well-being within the construction industry. It is worth mentioning that, given the limitations of our sample size, further investigations are needed to understand the direct impact of indoor environmental factors on productivity, health, and comfort. Future research endeavors should aim for larger-scale studies to further explain these relationships.

In summary, the primary audience for this project includes, but is not limited to, developers, business owners, architectural designers, engineers, general contractors, manufacturers, human resource strategy executives, timber marketers and investors, environmentalists, researchers, and policymakers. This primer offers valuable insights into the performance of MTC from the occupants’ perspective, complementing the overall understanding and promotion of timber construction. As such, it contributes to the future achievement of sustainability goals in construction practices.