Increased life expectancy and declining birthrates have caused the rapid expansion of an aging population. Moreover, because of common chronic diseases (eg, heart disease, stroke, cancer, dementia, and diabetes), the demand and costs required for the care of elderly people are immensely growing [1,2]. To diminish these care costs in a relatively effective way, the solution focus is shifting away from formal care in hospitals and care centers toward informal care in personal home environments [3] because of the cost-effectiveness of informal care and less intrusiveness in one’s personal life [4,5]. Elderly people often require frequent and immediate medical interventions to prevent emergencies through continuous monitoring of their physiological parameters and activities [6]. This continuous monitoring, which might cause a significant financial burden in the case of formal inpatient care, can be realized more comfortably through informal care using a smart home platform [7]. Highly developed information and communication technologies can make home environments intelligent and provide remote, nonintrusive health care monitoring [6].

Smart homes are being realized using ubiquitous computing and internet of things (IoT) technology, which connects devices and systems [8,9]. Previous studies have characterized the smart home as integrating technologies such as (1) home automation that allows devices and systems to be controlled automatically, (2) communication networks that connect the key electrical appliances and services, (3) remote access and control that allows the system to be operated at a distance, and (4) home intelligence that is aware of users’ individual contexts [10-13]. With those characteristics, scholars have defined the smart home’s purpose as providing a better home life experience by promoting safety, security, comfort, communication, and entertainment through technical management in the home environment [14,15]. Meanwhile, other scholars have pointed out the concerns over ethical and legal issues of smart home technologies regarding privacy, security, and confidentiality because of the highly identifiable nature of data [16-21]. Nevertheless, with a judicious approach to their ethical and legal risks, smart homes could be effective for continuous and remote monitoring of elderly health and for disease prevention, and they can reduce the costs of care for the aging generation while improving their independence and quality of life [2,3,22,23]. Various terms have been utilized to describe this technology, such as health smart home [24,25], U-health smart home [26], ubiquitous health care [6,27,28], and smart homes in or for (elderly) health care [2,3].

Meanwhile, the focus of previous research on smart homes has primarily been on the development and application of smart home technologies within the boundaries of computer science and engineering research [11,12,15,29-32] because smart home production is inherently technology-intensive [33]. Likewise, according to several literature reviews about health care in smart homes [2,3,22,34], smart homes for health care have largely been investigated from the perspective of technology application. Such studies have analyzed and classified literature on smart homes for health care according to the types of sensors, network or communication technologies, and the algorithm models of data processing [2,3,12].

However, health care services are cocreated by elderly residents’ experiences, and their experiences directly influence the perceived quality of the health care service [35,36]. Moreover, health care service experience is shaped by the interactions of elderly users with numerous touchpoints in the context of service [37]. In this sense, the viewpoints of service experience and service context are substantial in health care service, but they have not actively been engaged in research on smart homes for health care. Therefore, we accentuated the service experience and context perspectives of health care in smart homes in this study. To be consistent in our use of terminology, we adopted the term smart homes for health care services (SHHSs) and established an operationalized definition encompassing both technical and experiential viewpoints as follows: SHHSs are residences integrated with ubiquitous computing and IoT technology, which have the characteristics of home automation, communication network, home intelligence, and remote control and access by authorized health care personnel. They provide informal health care services such as real-time and long-term health monitoring, disease prevention by detecting anomalies, and unobtrusive activity support that does not interfere with individuals’ quotidian activities; thus, they reduce care costs, enable a satisfactory service experience in a private and comfortable home environment, and improve the independence of elderly residents.

The academic perspective of service experience originates from service management research. In this field, the significance of service environments and service context engaged with service experience has been emphasized, as the service provision and service interactions occur in such environments and contexts [38]. First, service interactions, widely called service encounters [39] in service management research, are direct or indirect interactions between customers and service providers. Service interactions have been underscored because they can be diversified according to individual customers’ varied past experiences and preferences as well as probable differences between service providers [40]. Second, service environment, which Bitner defined as the servicescape [41], is the physical and social environment where the service interactions take place, and the servicescape can influence the different ways in which customers perceive and experience a service [41,42]. Finally, service context refers to the social and cultural structures, such as social norms and institutions, which could influence the way a service’s stakeholders interact with each other [43,44]. Therefore, service experiences are created by the service provisions and service interactions in association with diverse service environments (ie, servicescapes) and are concurrently profoundly influenced by service context [38]. In other words, service experience could be cocreated by multidimensional combinations of those 3 layers—service interactions, servicescapes, and service contexts.

The main focus of this study—the servicescape is a fundamental and componential level in the creation of service experiences as it can serve as an inducing or restricting factor on usage behaviors. Consequently, it can influence the service user’s emotional response, perception of the intangible service quality, satisfaction with the whole service experience, and intention of continuous usage [42,45-48].

In line with the significance of servicescapes in service experience, the servicescape perspective is also required for SHHSs, which has the characteristics of both health care services and smart services. Generally, health care is a credence-based service and patients tend to have difficulty assessing the technical quality of service (ie, the professional credibility of medical care) [36]. Instead, functional quality (ie, the service quality as it relates to the physical environment—the servicescape) is the primary determinant that affects patients’ perception of the health care service process [35,37]. Regarding smart services, intelligent devices and environments communicate and collect data in real time based on advanced networks and pervasive computing technology [49,50], but data transfer and technological elements are invisible or intangible to service users. Furthermore, direct interactions between users and service providers (ie, service encounters) are largely supplemented or replaced by interactions with smart devices and environmental elements. Consequently, users are inclined to perceive the service quality and service experience from the environments of smart services—namely, the smart servicescape [51]—thus, from the direct, visible, and tangible interactions with the smart servicescape. In this way, health care services and smart services commonly have a particular significance of servicescape from the viewpoint of service experience; for this reason, this study used the concept of smart servicescape for SHHSs.

The importance of the smart servicescape in SHHSs can be supported from another perspective; the ecological approach for a complex adaptive system. Rouse defined a complex adaptive system as a nonlinear and dynamic system that is composed of independent and intelligent agents whose behavior patterns emerge rather than being designed into or controlled by the system [52]. He also stated that one cannot force or command such systems to abide by behavioral and performance directions. The health care service falls under this system because of its diversified stakeholders and interests [53]. Meanwhile, the smart home can also be regarded as a complex adaptive system for 2 reasons. First, it is a dynamic and therefore complex system consisting of diversified intelligent agents (ie, smart devices and environments) based on real-time communication. Second, the smart home is an adaptive system that is continuously customized in accordance with the emerging behavioral patterns of its resident users because it is a private space where usage behaviors cannot be easily controlled to comply with service providers’ intended directions. The SHHS can, therefore, be considered a complex adaptive system.

Then how can service experiences in a complex adaptive system such as an SHHS be understood? In the research field of service management or service design, service experiences have been analyzed and profiled, adopting service blueprinting or customer journey maps. Service blueprinting, pioneered by Shostack [54], is a diagrammatic approach in which the key activities and their linkages involved in service delivery are plotted. It clarifies the series of customer actions, physical evidence, and frontstage and backstage interactions to emphasize the perspective of service users [55,56]. Customer journey maps are also a diagrammatic method in which customers’ steps in engaging with multiple touchpoints in a service are illustrated [57]. These maps conceptualize service experiences as a chronological process of a customer’s journey with a service provider [58]. These approaches can provide an understanding of the sequential flow of tasks in a service itinerary (ie, the customer’s journey) that a service provider has intentionally designed. However, they may not be suitable for describing a complex adaptive system such as SHHSs, because diversified—hence unintended and undefined—behavioral patterns can be generated given the specificities of SHHSs (ie, multiple stakeholders, private home circumstances, and perpetual service duration for continuous health monitoring).

For this reason, the SHHS requires the ecological approach. This approach, which originated from Barker and Gibson’s ecological psychology theory [59,60], considers environmental and social factors as parts of a system. According to this approach, individuals are surrounded by a complex combination of physical and social variables that operate in both direct and indirect ways to influence human activities [61,62]. Vicente advocated for the ecological approach in the field of human-computer interaction (HCI) and claimed that a work analysis for complex sociotechnical systems needs to start with and prioritize environmental constraints [63]. Vicente classified the demands (or constraints) of human works into (1) cognitive constraints relevant to human cognitive systems such as mental models and (2) environment constraints that constitute the context in which humans are situated, such as their physical and social realities [63]. The dominant viewpoint in psychology and HCI has been the cognitivist approach, which emphasizes cognitive mental models such as the sequential flow of an instructional service itinerary. Alternatively, the ecological approach leads to the analysis of environmental constraints, and it enables individuals to understand the real context that may shape actual behaviors (ie, behavior-shaping constraints) [64] and allows them to deal with unexpected and variable situations [63]. Given that SHHSs are complex adaptive systems in which diversified and undefined behavioral patterns can be generated by complex combinations of contextual and environmental factors, the ecological approach is appropriate for understanding service experiences in SHHSs by identifying the smart servicescape. Considering the necessity of the ecological approach to SHHSs, this study proposed a conceptual framework of smart servicescape to delineate complex environmental elements of SHHSs.

Ahead of investigating the smart servicescape, the concept of servicescape needs to be clarified. As briefly mentioned in the Introduction, Bitner [41] defined the servicescape as a man-made physical and social environment in which service encounters are framed. Bitner emphasized the effects of physical environments and classified them into 3 dimensions: (1) ambient conditions (circumstantial attributes, such as temperature, air quality, noise, music, and odor); (2) space and function (the arrangement and layout of the machinery, equipment, and furnishings); and (3) signs, symbols, and artifacts (visible communicators on the exterior and interior) [41]. Since then, many scholars have explored the categorization of servicescapes in diverse service sectors (eg, restaurants, leisure, hospitality, and health care facilities) [45,47,65-67]. Furthermore, the social servicescape has also been underlined including social or noncommercial relationships, such as direct interactions with service providers, indirect interactions with other customers, social density, and connectedness [42,68].

Founded on the notion of servicescape embracing physical and social aspects, we had proposed the concept of smart servicescape regarding smart services in a prior study [51]. Analyzing the cases of smart home service experiences, new dimensions, including datascape, were introduced to reflect the key characteristics of smart services (ie, real-time data collection and the continuous data exchange of intelligent objects) [51].

Meanwhile, several studies have been conducted on the architecture of smart homes in association with health care services [2,3,6,26]. Researchers have commonly proposed a four-layer architecture for SHHSs even though their detailed elements or labels differ. Generally, they have agreed on the layers of (1) sensors and actuators, (2) communication or network, (3) computing or data processing, and (4) services. The layer of sensors and actuators is relevant to physical devices, such as the units of home automation and home control, biosensors, and environment sensors. The communication layer refers to the wired or wireless home networking required for information gathering, service discovery, and appliance discovery. The computing and processing layer pertains to the information analysis and machine learning technology engaged in knowledge management and decision making. Finally, the service layer varies from the types of health care services to those of health care service providers and organizations. Although the layered architecture represents the overall structure of the SHHS well, the criteria for classification of the 4 layers are not clearly defined. Moreover, the aforementioned studies have been conducted in computer science and engineering fields; therefore, the research focus lies more on a technical perspective investigating which types of technologies are applied in each layer. The ecological approach has been absent from previous studies; particularly, the perspective of service experience and that of smart servicescape have not yet been investigated in SHHSs.

To infuse the ecological approach with the understanding of service experiences in SHHSs—in other words, to delineate the extensive spectrum of environmental constraints in the complex adaptive system of SHHSs—we introduced a conceptual framework of the smart servicescape, the Smart Servicescape Wheel (SSW), as illustrated in Figure 1.

The Smart Servicescape Wheel for SHHSs globally classifies conventional servicescapes, such as the Physical scape and Social scape as perceptible servicescapes. The Datascape, which is a distinctive characteristic of smart services, is categorized as an imperceptible servicescape because its elements are hardly perceived by elderly residents unless they are intentionally visualized with certain service objectives. Moreover, the interactions that occur between the service user (ie, the elderly resident) and the perceptible servicescape can usually be recognized as direct interactions, such as the interactions of the elderly with smart devices (eg, physiological monitoring devices) or caregivers (eg, clinicians at health care centers and medical staff at hospitals). However, a large part of the interactions in the smart servicescape can hardly be perceived by the resident. These ambient interactions [69] are among the Datascape, Physical scape, and Social scape without the user’s direct intervention. Subsequently, the whole scope of direct and ambient interactions constitutes the cyber-socio-physical interactions [70].

Nevertheless, the focus of the SSW from the ecological perspective is not on the interactions diversely shaped in the spectrum of smart servicescape but on the detailed servicescape elements, namely the environmental constraints themselves. Moreover, the environmental constraints should be defined independently of any particular device, event, task, or interface because the ecological approach’s implication lies in designing a diverse spectrum of future service practices combining the environmental constraints rather than in designing a single flow of a service [63]. This implication implies that the smart servicescape elements need to be defined at the level of components or functions. Founded on this rationale, the Physical scape consists of (1) hardware components, (2) environmental cues, and (3) human states; the Social scape is composed of (1) service relationships and (2) social relationships; and the Datascape comprises (1) computing intelligence, (2) databases, and (3) communication networks. Accordingly, this section will discuss in detail each component of the SSW which is categorized in Table 1.

Despite the value and opportunities presented by the SSW, several limitations of the framework stem from its focus and conceptual nature. As noted in the Introduction, service experiences could be cocreated by multidimensional association among 3 layers: servicescape, service interactions, and service contexts. However, the focus of the SSW is limited in describing detailed servicescape elements rather than in determining the interactions that occur between those elements or defining probable influences from/on social and cultural structures (ie, service context). For the sake of service planning and development, the other 2 layers of service interactions and service contexts need to be profoundly investigated.

First, in terms of the service interaction layer, the next phase after defining the environmental components and functions could be the establishment of detailed interactions and activities shaped by the combination of smart servicescape elements. Direct interactions such as those between the service user (ie, the elderly resident) and the perceptible servicescape need to be identified. Furthermore, the ambient interactions among the imperceptible and perceptible servicescapes (ie, the Datascape, Physical scape, and Social scape) without the user’s direct intervention require a more comprehensive exploration considering the ambient characteristic of smart services. The layer of service interactions might allow us to consider innovative ways of direct and ambient interactions for more natural and user-centered experiences of SHHSs.

Second, regarding the service context layer, social and cultural structures such as social norms and institutions could influence the ways of service interaction and experience formation. Particularly, social structures and institutions pertinent to SHHSs need to be investigated in terms of ethical and legal issues because personal data collected through smart home technologies require a great degree of protection [17,20]. Therefore, norms, regulations, policy, and legislation systems in association with privacy, security, and confidentiality issues in SHHSs would require high attention in future research [93].

Third, as the SSW is a theoretically established conceptual framework, further empirical studies to evaluate the validity of the framework are needed; it should be applied in the development of a new system of SHHSs or in the analysis of real use cases of SHHSs. Moreover, because the SSW is defined at the conceptual component or function level, it is limited in its elucidation of real products or systems that could be the complete combination of smart servicescape elements. Therefore, further research on the association of the SSW components to describe the cases of actual products or systems could be possible.

Finally, although the aspect of Social scape was covered less extensively than other scape categories in this study, it does not mean that it is less significant. The Social scape has been investigated largely from the perspective of stakeholders in service research, and the stakeholders in SHHSs would be complicated considering their intricate relationships. Therefore, it could be required to explore the interplays of Social scape parties in association with the elements of Physical scape and Datascape.

This study asserted the value of an ecological approach with emphasis on environmental constraints for understanding SHHSs. This study is based on 2 rationales: (1) users tend to perceive service quality and service experiences through the servicescape because of the intangibility of health care and the pervasiveness of smart home services and (2) both service domains are complex adaptive systems in which diversified and undefined service experiences—not only a few intended service flows—can be generated by complex combinations of servicescape elements.

Accordingly, the conceptual framework of the SSW was proposed as an ecological approach delineating the extensive spectrum of environmental constraints in SHHSs. Generally divided into perceptible and imperceptible servicescapes, the SSW consists of the perceptible Physical scape (ie, hardware components, environmental cues, and human states), the Social scape (ie, service relationships and social relationships), and the imperceptible Datascape (ie, computing intelligence, database, and communication networks).

The strengths of the SSW lie in its various application opportunities. The SSW can be utilized in service planning and development to (1) establish the requirements for SHHS development, (2) associate with WDA by defining component layers, and (3) understand the real contexts of SHHSs to enhance the prediction of diverse service experiences, as well as in service management to develop measurement items for the operation and evaluation of SHHSs.