Human Behavior Adaptability in Responsive Buildings: An Exploratory Study in Workplace Settings

Abstract

The increased uptake of information and communication technologies (ICTs) is fostering the development of responsive buildings that are aware of and respond to human needs. Current approaches mainly focus on adapting building systems to enhance people’s comfort and energy performance. Little is known about how responsive buildings can inform human behavior adaptability to meet the diverse needs of individuals and organizations within built environments. This study recorded the outcomes of six multi-agent simulation projects exploring human behavior adaptability in different workplace settings. The results have been analyzed through the lenses of ‘place’ theory to extrapolate a framework for human behavior adaptability, jointly considering the characteristics of the spaces, the people that inhabit them, and their activities. This framework provides analytical insights on the design and development of adaptability strategies that consider non-linear interactions and dependencies between the characteristics of the built environment, the needs of the inhabitants, and the goals of organizations.

1. Introduction

Built environments are designed to optimally serve the needs of their inhabitants. However, while buildings are fundamentally static, human needs and behaviors are highly dynamic and continuously changing. A gap therefore exists between the affordances of built environments and the dynamic behavior of building occupants, potentially leading to diminished user satisfaction, operational inefficiency, and space over- or under-utilization. As people spend approximately 90% of their time in indoor environments [1], it is essential for buildings to become aware of—and responsive to—the dynamic needs of their occupants.

To improve alignment between people and built environments, organizations often consider redesigning and renovating their workplaces to enhance occupants’ satisfaction and productivity while also reducing operational costs [2]. A different approach entails adopting adaptive workplace management approaches to meet dynamic occupant needs and prevent costly, time-consuming, and environmentally damaging building redesigns [3]. This latter solution aims to foster mutual alignment between buildings and occupants to maximize the use of existing space resources while also enhancing people’s comfort and productivity [4]. The need for such an alignment has been accelerated by the COVID-19 pandemic, which introduced unprecedented flexibility demand to accommodate varying occupancy and workstyle needs of individuals and organizations, especially in working and learning environments [5,6,7].

Recent developments in information and communication technology (ICT) have been progressively introduced into the fabric of the built environments to inform management strategies in buildings [4,8] and cities [9]. Rather than static containers, buildings are progressively becoming ‘active partners’ that are aware of and responsive to the needs and preferences of their human inhabitants and respond accordingly to enhance their health and performance [10]. Prior studies demonstrated how sensor-equipped buildings and wearable devices can inform demand-based control strategies for mechanical and electrical services, improving occupant comfort and energy efficiency [11,12].

These approaches mainly leverage data collected via building sensors and wearable devices to inform the adaptability of physical building systems such as HVAC, temperature, and light to enhance energy-related performance and people’s comfort. Fewer approaches have explored how ICT-enhanced buildings can inform the spatial behavior of building occupants to enhance the overall performance of a workplace ecosystem, including the individuals, organizations, and the built environment at large.

The potential benefits of human behavior adaptability have been previously explored by Gath-Morad et al. [13], who investigated how smart and responsive environments impact pedestrians’ urban mobility patterns by providing information beyond pedestrians’ perceptual abilities. Sood et al. [14] developed a recommendation system for optimized seat selection in offices based on users’ environmental preferences. Nevertheless, a framework to explore workplace adaptability strategies focused on human spatial behavior to improve the overall performance of a workplace ecosystem still needs to be developed. To address this gap, the following research question (RQ) is formulated: “How can human behavior adaptability strategies in responsive buildings be developed and analyzed while considering the non-linear interactions and dependencies between the built environment, the occupants, and their activities?”.

Following a research-through-design approach [15], fifteen novice architects participated in a simulation study to develop human behavior adaptability scenarios in responsive buildings. By analyzing the simulation outcomes using thematic analysis through the critical lens of ‘place theory’ [16,17], this paper contributes a framework for human behavior adaptability strategies in responsive buildings that jointly consider spatial, social, and operational aspects across workplace settings.

2. Literature Review

2.1. Human Behavior in Built Environments

Buildings are not merely physical objects; they are environments that host a variety of occupants engaging in co-located activities. Various disciplines in architecture, social science, anthropology, and environmental psychology have explored the dynamic interactions between individuals and their surroundings. Notably, ‘place theory’ provides a comprehensive approach to understanding human behavior in built environments [16,17]. Canter [17] defined ‘place’ as the confluence of space, a set of activities carried out in that setting, and the people who perform them. Kalay [18] defined ‘place’ as a setting that affords human activities, while affecting (and being affected by) social and cultural behavior. Harrison and Dourish [16] elucidated that ‘places’ are higher-level ensembles including spaces, their inhabitants, and the activities taking ‘place’ in them. The act of ‘placemaking’ can be defined as a conscious process of arranging the components of the built environment to support human activities while also conveying the social and cultural conceptions of the inhabitants [17]. The concept of place has been applied to analyze how built environments can promote a sense of belonging and attachment in workplace settings [19]. Other approaches focused on representing places that no longer exist [20] or are yet to be built [21] to inform design decisions.

Place theory collectively emphasizes three mutually dependent components for analyzing and improving alignment between people and built environments: (a) space, encompassing the physical and environmental properties where behavior occurs; (b) people, focusing on the roles, preferences, and conceptions of the built environment’s inhabitants; and (c) activity, considering the tasks people undertake to fulfill their own needs or the ones of an organization within a building.

The process of alignment between the three components in workplaces has been explored through person–environment (PE) fit theories [22], also defined as employee–workplace alignment theories [23]. These approaches provide an ecosystem-level perspective to explore human behavior in built environments. However, a framework providing practical guidance to explore workplace adaptability strategies in responsive buildings capable of sensing and responding to human needs is yet to be developed.

2.2. Current Approaches for Workplace Adaptability

Adaptability can be defined as follows: “The capacity of a building to accommodate effectively the evolving demands of its context, thus maximizing value through life” [24]. Traditional adaptability strategies have focused on the physical aspects of buildings [25,26]. These approaches, however, are expensive, time-consuming, and unsuitable for rapid responses to sudden shifts between service demand and resource availability. Evidence-based approaches have been used to inform swift adaptability strategies based on knowledge gained from past experiences [27]. Post-occupancy evaluation (POE), for example, is an established method of gleaning insights into a facility’s performance to recommend operational improvements [28]. Nevertheless, solutions that may have proved effective in the past may not suit new situations.

Simulation approaches have been employed to predict and analyze workplace adaptability strategies [29,30]. Among them, multi-agent simulations represent occupants as goal-oriented synthetic agents interacting with themselves and their surrounding environment [31]. Several approaches focused on simulating occupant comfort and energy efficiency [32,33], while others concentrated on people’s movement and activities to measure occupants’ experience and operational efficiency [34,35,36,37,38]. These methods, however, help architects predict and evaluate adaptations mainly requiring physical building changes or renovations. A different approach is needed to inform dynamic adaptations in existing building ecosystems to inform everyday occupant behaviors.

2.3. Frameworks for Responsive Workplace Environments

Advancements in information and communication technologies (ICTs) have facilitated a systematic study of human behavior in buildings to support a variety of applications, including occupant presence and behavior analyses [39,40,41,42], space–use matching [14], and building systems automation [43,44]. The integration of sensor data with digital building models has given rise to ‘digital twin’ systems, providing a real-time overview of the current state of a facility for building management [45,46] and sustainability assessments [47]. Other studies explored the interactions between people and adaptive building components, such as façades, lighting systems, and movable partitions, to enhance comfort and people’s experience [48,49]. More broadly, human–building interaction (HBI) studies investigated the reciprocal adaptability between buildings and people to enhance the inhabitants’ quality of life [50] with a predominant focus on energy efficiency [51].

Becerik-Gerber et al. [10] proposed an interdisciplinary framework encompassing critical domains to human–building interaction (HBI) research. Alavi et al. [50] delineated three crucial dimensions of HBI—people’s experiences, built environments, and computing devices—each further dissected into physical, spatial, and social aspects. Nguyen et al. [49] explored spatial adaptations’ impact on fundamental place dimensions—spatial, situational, and subjective qualities. Meanwhile, Achten [48] introduced the concept of ‘interaction narratives’ as structured sequences delineating interaction moments between users and building systems.

While these approaches predominantly focused on the capabilities of building systems to respond and adapt to human needs, fewer approaches have explored, tested, and conceptualized a framework for human behavior adaptability that leverages the awareness of responsive buildings for occupant presence and activities to inform their behavior and enhance the overall workplace performance.

3. Materials and Methods

This research aimed to develop a practical framework to guide the analysis and development of human behavior adaptability strategies in responsive buildings that consider the mutual interactions and dependencies between the fundamental components of a place, namely the space, the people inhabiting it, and the activities they perform. To address this goal, the methods involved the following steps: (a) developing a multi-agent simulation system to analyze human behavior in responsive buildings; (b) simulating scenarios of human behavior adaptability in responsive buildings; (c) analyzing the simulation outcomes through the lenses of place theory to extrapolate a framework for guiding the analysis and development of human behavior adaptability strategies in workplace settings; (d) testing the framework’s ability to reveal relations and dependencies between the components of ‘place’ across different stages of the adaptability process.

3.1. Multi-Agent Simulation of Human Behavior in Responsive Buildings

A multi-agent system (MAS) has been developed to simulate human behavior adaptability in responsive buildings that are capable of sensing and responding to human presence and activities. Building occupants have been modeled as computational agents associated with a specific role within a workplace setting. For example, in an academic library scenario, agents can represent students and library staff members. Agents participate in various narratives—sequences of activities to accomplish individual or group goals [52]. Narratives orchestrate agents’ behavior to ensure collaboration across agents participating in the same narratives. They also adapt their execution while considering agents’ profiles and evolving built environment conditions. For example, a narrative involving a student seeking a table at the library provides the following factors: it accounts for the student’s social and environmental preferences; it considers the current social and environmental conditions; it identifies a suitable table that is visible from the student’s current position meeting the students’ criteria; it guides the student to the table; it initiates a study activity.

The fundamental components of a narrative-based system are as follows:

• A space model that encompasses a building layout, the affordances of each space, its components (e.g., furniture, equipment), indicating the activities they support, and the prevailing environmental conditions.
• A people model that considers occupant profiles, including organizational roles (e.g., a student, librarian, customer, shopping assistant) and preferences (e.g., social attributes, environmental preferences, etc.).
• An activity model that includes people’s actions, such as moving, stationing, interacting, and waiting. People’s movements are modeled using the A* algorithm to find the shortest routes while circumventing static and dynamic obstacles. Structured sequences of activities form narratives that aim to achieve higher-level objectives. For example, a narrative involving a student seeking a table in a library involves navigation to the study area entrance, identifying an optimal table based on global knowledge (in the case of a responsive building), studying, and leaving.
• A narrative management system coordinates multiple narratives, assigns priorities to them, and resolves conflicts among narratives concurrently, requesting control of the same agents.
• A simulation output visualizes occupants’ dynamic behavior and quantifies project-specific key performance indicators (KPIs), assessing the aspects of a workplace performance.

The simulation system integrates several software tools: Rhinoceros 3D (version 7) for space modeling; Unity 3D (version 2021.2.6) for user, activity, and narrative modeling, interaction computation, and analytical results generation; Unity Visual Scripting (incorporated into Unity 3D version 2021.2.6) to enable narrative modeling for people without a coding background. Customized Visual Scripting components have been coded in C#. Figure 1 provides an overview of these simulation components.

3.2. Data Collection

A combination of research-by-design [15] and simulation [18] has been used to develop scenarios of human behavior adaptability in responsive buildings, since they cannot be tested in practice due to practical, methodological, and technical challenges. Since ICT-enhanced buildings are mostly under development, this study did not consider specific technologies for sensing and communication. Instead, it considered hypothetical scenarios in which such technologies are already equipped in a building to test their possible implications for human behavior adaptability.

Fifteen novice architects participating in an academic course for senior and graduate students in the Faculty of Architecture and Town Planning at the Technion, Israel Institute of Technology, took part in this study. They used multi-agent simulation to design human behavior adaptability scenarios in responsive buildings, which can inform occupant behavior based on a comprehensive understanding of a building, its inhabitants, and unfolding situations. The process involved the following steps: (a) collecting data via field observations and literature reviews to identify typical human behavior patterns in various settings; (b) using multi-agent simulation to simulate these patterns in traditional buildings; and (c) developing and simulating human behavior in responsive buildings that can sense unfolding situations and recommend dynamic adaptations to meet user needs.

Seven projects were developed by teams of 1–4 members over the course of thirteen weeks, meeting weekly for three hours. Six of seven teams voluntarily contributed their data for this study, so only their projects were considered. Ethical approval was obtained by the Institutional Review Board for Social and Behavioral Sciences at the Technion—Israel Institute of Technology.

3.3. Data Analysis

Comprehensive projects’ data, including diagrams, simulation output videos, and snapshots of project progression were collected and analyzed to explore the capabilities and benefits of human behavior adaptability in responsive buildings to enhance the performance of a building and its inhabitants. A qualitative approach was used to analyze the simulation study outcomes because of its suitability in exploratory studies, seeking deeper comprehension of emerging phenomena [53]. Specifically, thematic analysis [54] has been used to identify, code, and organize key human behavior adaptability themes along three dimensions reflecting the different stages of the adaptability process: situational awareness, behavior adaptation, and outcome evaluation. Situational awareness involves understanding the context where human behavior takes place from a building’s perspective, surpassing the individual perception of each building occupant. Behavior adaptation informs the behavior of building occupants based on insights gathered through situational awareness to achieve individual and organizational goals. Outcome evaluation considers the broader and non-linear effects of human behavior adaptability strategies on the entire building ecosystem, including the building, the inhabitants, and their activities. These dimensions, characteristic of the design of intelligent and adaptive systems that respond to unfolding situations [55], form a closed-loop system that systematically evaluates unfolding situations and devises adaptation strategies to meet diverse user needs (Figure 2). The number n in the Section 4 indicates how often the theme has been identified across the projects.

3.4. Framework Development and Testing

To create a comprehensive framework for developing and analyzing human behavior in built environments, the identified dimensions and related themes have been organized based on the three critical components of a place (discussed in Section 2.1), which capture the relationship between a building, its occupants, and the activities they perform. The emergent framework combines a practical understanding of the dimensions needed to develop a behavior adaptability strategy with theoretical grounding in place theory; this explores the interactions among spatial, social, and operational components within and across adaptability dimensions. The framework has been applied to analyze the adaptability scenarios developed via multi-agent simulation, to identify synergies and non-linear interactions across the spatial, social, and operational components of a place.

4. Results

Six simulation projects demonstrated scenarios of human behavior adaptability in different workplace settings. The results indicated that responsive buildings that are aware of people’s social and environmental preferences, occupancy levels, and environmental conditions could recommend optimal workstations in a library (Team B) and study area (Team C). Responsive buildings that are aware of people’s social preferences could match people with similar interests (Team A) and identify the most favorable time and location to foster (or prevent) social interactions with co-workers (Team D). In mission-critical facilities such as retail centers (Team E) and healthcare facilities (Team F), responsive buildings could improve service efficiency, enhancing user experience and business outcomes for the workplace organization. Figure 3 shows a simulation screenshot for each developed project.

4.1. Themes of Human Behavior Adaptability in Responsive Buildings

Various themes of human behavior adaptability have been identified and categorized for each dimension of the adaptability process: situational awareness, behavior adaptation, and outcome evaluation. Figure 4 provides an example of each theme organized along three adaptability dimensions in four selected projects.

4.1.1. Situational Awareness Themes

Five situational awareness themes have been identified.

Preferences (n = 6): These describe how responsive buildings can consider the individual preferences of their occupants related to contextual conditions, including environmental conditions, social interactions, group affiliations, and task execution modalities. For example, Teams B and C considered the preferences of occupants for noise, light, and thermal conditions. Team D considered the preferences of individuals to engage or avoid social interactions in the workplace. Team A considered the interests of conference participants seeking interactions with people with affiliated interests. Team E considered the preferences of retail customers to be helped or not by shopping assistants. Team F considered the loneliness preferences of elderly people in long-term care facilities.

Resource allocation (n = 3): This describes how responsive buildings can monitor the location and availability of key building resources such as worktables or sitting areas, which can be dynamically allocated to meet people’s needs. For example, Team A considered the dynamic availability of sitting spots at dining tables to identify pairing opportunities among participants’ groups. Teams B and C considered the availability of sitting spots at worktables to allocate individuals and groups to study areas.

Environmental factors (n = 3): These describe how responsive buildings can detect prevailing environmental conditions, such as light, noise, temperature, and spatial congestion in a space or a specific area within it. For example, Teams B and C considered light, noise, and temperature preferences in working and study areas to help users identify a worktable matching their preferences. Team D considered spatial congestion to inform the time and location of office workers’ breaks to foster or mitigate social encounters.

Process (n = 2): This describes how responsive buildings can track the unfolding of a process aimed at meeting the needs of an individual or an organization within a building, including the waiting time of building occupants to receive a service. For example, Team F considered shopping assistants serving customers in retail centers. Team E considered volunteers visiting elderly people in nursing clinics. Both tasks require the systematic visit of different users waiting to receive a service. The responsive building can keep track of the process while considering the number of users requiring service and their waiting times.

Status (n = 1): This describes how responsive buildings can consider the social, psychological, and health conditions of building occupants that dynamically unfold based on contextual situations. For example, Team F considered the loneliness status of elderly people in nursing facilities, which depends on the last time they have been visited.

4.1.2. Behavior Adaptation Themes

Four behavior adaptability themes have been identified.

Scheduling (n = 3): This describes how responsive buildings can identify the most appropriate activity, the time to execute it, and the task sequence depending on the surrounding social and spatial conditions. For example, in Team D’s project, the responsive building informed workers about the optimal time and location to perform a work break to satisfy the occupants’ preferences for maximizing or minimizing the chances of social interactions. In Team E’s project, the responsive building directed the behavior of shopping assistants to interact only with customers who specifically expressed their desire to be helped. In Team F’s project, the responsive building recommended a volunteer an optimal sequence of elderly people to visit based on their loneliness status.

Location selection (n = 3): This describes how responsive buildings can recommend the optimal location to perform an activity that matches the specific preferences and goals of the occupants. For example, in Teams B and C’s projects, the responsive building dynamically evaluated the environmental conditions of all possible worktables in a study area and recommended the one that best aligns with the preferences of individuals and groups. In Team D’s project, the responsive building informed workers about the optimal location to perform a work break based on their preferences for spatial density.

Function attribution (n = 1): This describes how responsive buildings can regulate the availability of spaces by dynamically selecting the function of a space or room, based on its affordances as well as people’s demand. For example, in Team C’s project, the responsive building dynamically changed the function of a space to provide occupants with an additional study area that matches their environmental preferences.

Group formation (n = 1): This describes how responsive buildings can inform the creation of people groups with similar interests to foster social interactions and productivity. For example, in Team A’s project, the responsive building dynamically matched groups of people with similar research interests to promote interactions at an academic conference.

4.1.3. Outcome Evaluation Themes

Three outcome evaluation themes have been identified.

Experience (n = 6): This describes how responsive buildings can enhance the experience of building occupants in terms of physical comfort, well-being, and even a sense of equity and inclusion. For example, Teams B and C aimed to enhance students’ comfort in a library and study area. Team D aimed to improve the social experience of workers in break times. Team E aimed at improving customer experience. Team F aimed to enhance the well-being of elderly people in nursing care facilities. Team A aimed to enhance the experience of conference participants by matching them with peers with similar interests.

Efficiency (n = 2): This describes how responsive buildings can improve process efficiency to meet the goals of individuals and organizations within a building. For example, Team E aimed to improve the service of shopping assistants to enhance customer satisfaction. Team F aimed to optimize a patient’s visiting procedure to enhance the quality of service to the elderly.

Resource Utilization (n = 1): This describes how responsive buildings can improve the utilization of building resources, including spaces and equipment, preventing over- and under-utilization. For example, Team C aimed to adapt the utilization of multi-functional rooms to match the specific needs of the occupants, therefore enhancing their utilization rates.

4.2. A Framework for Human Behavior Adaptability

A practical framework for developing and analyzing human behavior adaptability strategies is presented, which organizes the themes discussed in Section 4.1 into three cardinal components of place theory for each adaptability dimension. For example, the combination of the situational awareness dimension with spatial, social, and operational components of place theory gives rise to three new concepts: spatial awareness, social awareness, and operational awareness. These are each defined and exemplified through the themes identified in Section 4.1. A similar process is followed for the other two dimensions of human behavior adaptability. The emergent framework explores the dependencies and combined effects between spatial, social, and operational factors within and across dimensions (Figure 5). The following sections expand on each dimension and related components.

4.2.1. Situational Awareness

Situational awareness provides an ongoing understanding of unfolding situations involving the people in a space, the spatial and environmental conditions surrounding them, and their activities. In responsive buildings, situational awareness can be informed by various sensors and wearable devices that collect data about aspects of ongoing situations in a building. Such a perspective surpasses the awareness of individual inhabitants, which is limited to the perception of their surrounding context. Beyond informing the adaptability of physical building systems, situational awareness can inform the adaptability of human behavior to achieve alignment between a static building design and the dynamic activities of its occupants. Consistent with Endsley’s framework defining situational awareness as the perception of elements within built environments, the comprehension of their meaning, and the projection of future status [56], this dimension emphasizes understanding the conditions within an environment rather than decision making. However, unlike the original focus on human operators, this approach targets the design of intelligent systems embedded within built environments to aid occupants’ decision making. Moreover, this study considers the three-way interactions among spatial, social, and operational components, akin to Bardram and Hansen’s [57] context-based social awareness model for shared work environments. Situational awareness can be described as the integration of three mutually interacting components.

Spatial awareness: This encompasses an ongoing understanding of the spatial context for human behavior, including the status of building systems (e.g., HVAC), the allocated function to multi-functional spaces, the location of resources and movable equipment, and the prevailing environmental conditions in terms of light, temperature, and acoustics. Unlike other approaches [58], this conceptualization incorporates environmental attributes since they offer critical data to evaluate space characteristics and guide their utilization.

Social awareness: This considers the profiles and preferences of building occupants including their organizational roles, expected activities, environmental preferences, and social relations with other occupants. This conceptualization builds upon prior work that identified people’s preferences as influential factors for adaptive building systems [59,60,61], particularly in responsive environments [62].

Operational awareness: This centers on understanding the specific activities conducted within built environments dependent on the organization that occupies the building. It encompasses information about ongoing tasks, schedules, inter-task dependencies, performance goals, and their alignment with the organizational context. It is particularly meaningful in mission-critical settings such as healthcare facilities, retail centers, and workplace settings, where operational efficiency determines adaptability requirements. This approach extends beyond activity recognition systems focused on individual occupants [63] to encompass a more comprehensive corporate outlook, which is crucial for understanding how tasks contribute to broader organizational objectives.

4.2.2. Behavior Adaptation

Behavior adaptation informs the individual and group behavior of building occupants. Based on the awareness of unfolding situations, responsive buildings can calculate optimal strategies for space utilization, interpersonal interactions, and activity selection and execution method, and communicate it to users so they can adapt their behavior accordingly. While often considered separately, these human behavior adaptability strategies can be considered jointly to account for the mutual impact they may exert on each other. Human behavior adaptability complements the adaptability of building systems at the facility or room levels with a more granular approach that considers the behavior of each occupant, potentially achieving more accurate outcomes. This concept holds the potential for realizing the goals of intelligent environments by coordinating adaptability across a building ecosystem [64,65]. Human behavior adaptation can be described as the integration of three mutually interacting components.

Spatial adaptation: This involves a modification of the spatial context where an activity occurs. It includes identifying an optimal location to perform an activity as well as considering alternative functions for the same space, leading to changes in human behavior accordingly. Therefore, the proposed conceptualization is akin to the one provided by Sood et al. [14], where spatial adaptation entails informing people’s behavior to best identify and utilize existing locations, rather than adjusting building components, as explored by Nguyen et al. [49].

Social adaptation: This regulates group formations and social interactions among individuals by pairing groups and individuals with similar or complementary profiles to achieve individual or collaborative tasks. Prior studies recognized the impact of group dynamics and social connections on productivity, individual experiences, and organizational performance [66]. However, the dynamic orchestration of group formations in responsive buildings is yet to be fully explored.

Operational adaptation: This involves selecting activities and adapting their execution to contextual situations. It may entail prioritizing tasks, managing concurrent activities, and optimizing resource allocation—a challenging task in dynamic environments where limited resources (i.e., spaces, people, and equipment) must be shared across independently coordinated activities. This contextualization aims to extend established approaches to managing operations and resources at the organizational level [67] by linking operational goals with space utilization and occupant profiles.

4.2.3. Outcome Evaluation

Outcome evaluation encompasses the broader effects of human behavior adaptability on the building ecosystems, including the built environment, the occupants, and the organization occupying the building. It considers the integration of spatial, social, and operational benefits, mutually reinforcing each other to achieve heightened advantages for individuals, the organization, and the environment at large. Achieving holistic benefits requires recognizing and understanding the interdependencies and non-linear interactions among adaptability outcomes to maximize the combined effects on individual well-being, organizational efficiency, and productivity. Outcome evaluation can be described as the integration of three mutually interacting components.

Spatial evaluation: This focuses on maximizing the efficient use of space. It involves reducing over- and under-utilization to maximize the use of available resources and limiting energy consumption [30], ultimately minimizing costly renovations [68], while also accommodating occupancy fluctuations [5].

Social evaluation: This encompasses the improved health, well-being, and experience of individuals while recognizing and reconciling the different needs and preferences of the occupants. Previous research extensively explored how built environments impact occupants’ health and comfort [69], especially regarding air quality [70] and social distancing [71]. Despite existing evidence, achieving people-centered outcomes is challenging due to occupant diversity in terms of needs and preferences.

Operational evaluation: This concentrates on maximizing the efficiency and effectiveness of people’s tasks, aligned with organizations’ goals in mission-critical workplace settings. Alongside individual occupants’ outcomes, responsive buildings must consider the objectives of the occupying organizations. This necessitates a corporate viewpoint, including quantifiable performance metrics to gauge process efficiency. Understanding the structure, components, and objectives of the organization is thus essential, including conflict resolution strategies among competing goals to achieve congruent organizational performance [67].

4.3. Framework Testing

The framework has been tested to analyze human behavior adaptability strategies and explore dependencies and interactions among the three place components within each phase of the adaptability process and across dimensions. Figure 6 provides an example of such an analysis for three representative projects.

4.3.1. Synergetic Effects within Each Dimension

An analysis of the simulation projects via the proposed framework revealed that social awareness had been consistently considered across all projects as it aimed to evaluate specific external conditions that could be spatial or operational through the lenses of individual experience, status, and expectations. For example, Team B coupled spatial awareness of environmental conditions with social awareness of people’s preferences for those conditions to inform optimal table selection in workplaces and study areas. Similarly, Team F combined social awareness of the physical and psychological status of nursing home residents with operational awareness of their waiting times to be cared for to inform dynamic prioritization of caring procedures.

Synergies across components could also be identified in the behavior adaptation dimension. For example, in Team D’s project, the responsive building continuously monitored the spatial density across different break areas in a workplace setting and informed a joint operational and spatial adaptation strategy to determine the optimal time and location to take a break to satisfy workers’ preferences.

Synergetic interactions across components could also lead to more holistic outcomes. For example, in Team C’s project, combined spatial and social outcomes fostered space utilization while jointly improving people’s experience. Similarly, operational outcomes bolstered service quality for retail customers and elderly people in nursing clinics, enhancing, in turn, their satisfaction (Team E) and well-being (Team F).

4.3.2. Non-Linear Dependencies across Dimensions

The analyzed human behavior adaptability scenarios exhibited different strategies, revealing non-linear interactions across dimensions. While Team A proposed an adaptability strategy centered on social awareness, adaptability, and outcomes, the other projects explored non-linear interactions across components within dimensions, revealing different adaptability patterns consistent across building types. For example, Teams B and C focused on table selection in learning environments. They relied on a combination of spatial and social awareness for environmental preferences to inform the selection of a work desk leading to social and spatial outcomes including people’s experience and space utilization. Team D focused on the process of social interaction regulation in workplaces. It leveraged social and spatial awareness of interaction preferences and spatial congestion to inform spatial and operational adaptability related to the time and location breaks, resulting in social outcomes such as people’s experience. Teams E and F focused on service optimization in mission-critical facilities such as retail centers and healthcare settings. They leveraged social and operational awareness of people’s preferences and operational processes to inform operational adaptability aimed at improving process efficiency, which, in turn, affected social outcomes including people’s experience and well-being.

5. Discussion

This study explored the development and testing of a framework for human behavior adaptability in responsive buildings, which are aware of unfolding situations and can inform adaptability strategies to achieve optimal outcomes for individuals and organizations within a building. Different from traditional buildings, responsive buildings can inform adaptability strategies based on a comprehensive understanding of the dynamic state of a building facility, which transcends the perception and awareness of individual occupants. As a result, they may lead to improved outcomes for individuals and organizations.

Six simulation projects explored human behavior simulation scenarios in different types of workplaces. The simulation scenarios unexpectedly revealed insights about crucial societal themes such as equity and inclusion. For example, Team A showcased the capability of a responsive building to match individuals with similar research interests, regardless of the number of individuals sharing the same interests. Therefore, diverse groups with popular or specialized interests (thus, potentially a minority group) could enjoy similar benefits. This level of equality is unattainable in traditional environments, where the chance of individuals with niche interests encountering like-minded peers in social events is minimal. Thus, responsive buildings reveal the potential to equitably meet the needs of occupants with diverse profiles, reflecting inclusive principles in built environments [72].

This study presents certain limitations. Using the proposed framework to associate adaptability themes with specific spatial, social, and operational components within a dimension has been challenging due to the three-way interaction among components. For example, spatial density is a feature of the built environment that combines spatial and social information. However, in this project, it has been considered mostly as part of the spatial component since it ignores the profiles and preferences of individuals beyond their mere presence in space. Similarly, adaptability strategies such as group formation mutually consider spatial and social components. While the main drive for adaptability is the aim to form a new group, the act of gathering is inherently spatial as it leads to a joint table selection process. In this case, adaptability has mostly been considered social as its fundamental motivation. Furthermore, the proposed framework necessitates further testing since it is derived from and tested on a limited number of scenarios.

Other limitations pertain to the development of simulation scenarios. The simulation projects considered in this study explore hypothetical cases where sensing and communication technologies are already available in the considered building. However, ICT-enhanced buildings are still under development. Despite the rapid progress, such widespread applicability in buildings is yet to be demonstrated. Additional limitations pertain to the computational process used by responsive buildings to identify human behavior adaptability strategies in the simulated studies: it assumes complete and exact situational awareness, adopts a greedy approach to locally optimize for selected metrics without considering broader impacts on the spatial and social context over time, and recommends individual or group adaptations without synchronizing recommendations potentially conflicting with one another. Additionally, it lacks learning capabilities from past decision outcomes, assumes full compliance of building occupants with the provided recommendations, and resolves group preferences by averaging individual preferences. Future developments should consider incorporating more advanced optimization methods to inform workplace adaptability.

Lastly, this study analyzed projects that focused on how individuals adapt within predetermined spatial and social settings. Future research will combine human and building adaptability strategies, incorporating dynamic building elements like shading systems, movable furniture, adaptable lighting solutions, and acoustic panels. Furthermore, this study has not considered the interaction interface between occupants and responsive buildings. A possible extension of this work could explore the development of systems to proactively nudge building occupants [73].

Despite these shortcomings, the proposed framework could provide practical assistance to architects, designers, engineers, and computer scientists in jointly designing interactions, embracing a holistic perspective that considers the interconnectedness between spaces, people, and activities. In addition, it can inform the development of new sensing and responsive building management systems that complement the capabilities of existing technologies to enable awareness and adaptability across the different components and dimensions represented in the proposed framework. This process is expected to effectively transform buildings into adaptive systems that optimize resource utilization and adapt to evolving needs. More broadly, this framework could facilitate a more systematic development of human–building interactions, paving the way for future research endeavors to accelerate a transition toward more livable and sustainable environments.

6. Conclusions

This study aimed to develop and test a framework for human behavior adaptability in responsive buildings, which are aware of unfolding situations and can inform adaptability strategies to achieve outcomes for individuals and organizations. It examined the output of six simulation scenarios to identify themes categorized across three fundamental dimensions of adaptability: situational awareness, behavior adaptation, and outcome evaluation. These dimensions establish a closed-loop system that systematically evaluates situations and proposes adaptability recommendations, accounting for diverse user needs. Then, each dimension and theme has been analyzed through the lenses of ‘place theory’ to contribute a comprehensive framework for developing human behavior adaptability strategies considering spatial, social, and operational aspects—the constituting elements of building ecosystems. The framework has been tested to explore synergies, dependencies, and interactions across adaptability dimensions and their components.

Findings indicate that the proposed framework can be used to identify meaningful synergies within and across adaptability dimensions, enabling a novel way to categorize and develop adaptability strategies. This approach holds promise to provide a more systematic and streamlined approach for developing adaptability strategies, paving the way for future work aiming to promote a transition toward responsive environments that cater to human needs.