Smart Home Technology Diffusion in a Living Laboratory

Abstract

Smart home products continue to rise in popularity but have yet to achieve widespread adoption. There is little research on how the general population perceives benefits of different smart home devices beyond general surveys. Using a living laboratory of five solar houses that we equipped with a range of smart home devices, we assessed how university student residents learn about, use, and gain interest in adopting this smart home technology. Analysis of data confirms that users find lifestyle benefits to be the most important motivators for adopting smart home technology. Yet without training in using that technology, these benefits do not outweigh the risks associated with learning to operate that technology.

Keywords

adoption diffusion innovation smart home social psychology technical communication technology

Introduction

Smart home products are becoming widely available. They are in box stores, advertised on television, and dropping in price. Despite those facts, they have not been widely adopted by the general public, although many have suggested that smart home products will be the next major technology market (Greenough, 2016). For example, a 2017 survey conduct by PwC (PricewaterhouseCoopers) found that while 81% of survey respondents were aware of smart homes, only 26% wanted one (Takahashi, 2017). Although the market has grown consistently larger, publications such as Business Insider report that,

The US smart home market has still yet to meet the expectations many observers had in the early part of this decade. The same issues BI [Business Insider] Intelligence first identified back in 2015 still plague the space—persistently high prices, technological fragmentation, and consumers’ lack of a perceived benefit from the devices. (Shields, 2018, p. 1)

This quote speaks to Rogers’ (1995) definition of risk in technology diffusion among product users—namely, the certainty or uncertainty of attaining a goal in relation to its potential benefit. Therefore, ongoing research on smart home technology users will have important implications for technical communication scholarship and practical implications for business and governments. Regardless of smart homes’ growing availability, it is important to understand more about how the potential users learn about and adopt the technology that comprises a smart home.

We define smart homes as the integration and interaction of home products that allow for home automation, various methods of control, data collection, and an increasingly interactive environment for residents. Because those products range from automated lights to sophisticated security systems and from efficient money-saving utility panels to refrigerators that play music, smart products can be beneficial in a variety of ways but may also be seen as frivolous indulgences if communication highlighting their benefits does not accompany them.

As smart home products are just coming into the greater public’s view, now is an excellent time to study them. They are widely advertised by manufacturers and promoted by home builders as a major boon to would-be buyers, meaning that more and more people are being provided with smart home technology. But the general population, most of whom do not own smart home products, are just now beginning to show interest in them, which is creating a greater demand for research and information designed to inform policy makers, product designers, home builders, and consumers who wish to promote or adopt smart home products that have significant lifestyle, environmental, social, or productive benefits.

However, few studies concerning actual users of smart home technology in their own living environment have been conducted. Those studies reported that people adopt smart home products for specific instrumental benefits including saving energy and therefore money (Mennicken & Huang, 2012; Oliveira et al., 2015), enhancing security (Brush et al., 2011; Oliveira et al., 2015), saving time (Mennicken & Huang, 2012; Oliveira et al., 2015), and making life easier (Brush et al., 2011; Oliveira et al., 2015). People also adopt smart home technology for more general, affective reasons, including enjoying feeling technological (Mennicken & Huang, 2012; Oliveira et al., 2015), in control (Brush et al., 2011; Mennicken & Huang, 2012), that smart home products are fun to use (Oliveira et al., 2015), and that smart homes are modern homes (Mennicken & Huang, 2012).

In addition, little research has been conducted concerning how technical communication as training for smart home products impacts their use. Most smart home technology products are accompanied by little information out of the box other than basic installation instructions. If we accept that, “As technical communication researchers have traditionally conceptualized instructions, the purpose of these documents is primarily to train or educate a user to perform a task” (Longo, Weinert, & Fountain, 2007, p. 448), then the technology traditionally ships with very little instructional information. Amazon’s Alexa, for example, comes with little more than instructions for connecting the device to your local Wi-Fi.

Although many manufacturers post information on their websites, that information typically falls well short of the training required to set up the more complex, integrated features of multiple devices, focusing instead on what purchasing the items can do for your household. This oversight is particularly salient when considering that smart home technology has exponentially more options than more traditional technology given their capacity to network and interact. In essence, this transfers the communicative responsibility for training and uncertainty reduction onto the consumer. Therefore, the lack of accompanying technical communication is one of the most prominent features of smart home products. While there are hundreds of YouTube videos and website tutorials dedicated to providing that training, most are produced by individuals rather than by the manufacturers. This leads to the question, how much effort are people willing to exert to integrate smart home technology into their lives?

In this article, we will discuss the current literature regarding smart home technology as well as current models of technology diffusion that may be applied to studying the adoption/rejection of smart home technology, and we will report the results of our own study as it compares to previous research with smart home residents.

Two questions are of primary importance:

How likely are residents to adopt smart home technology when they are provided with that technology but not provided with training to accompany it?

How do residents provided with smart home technology learn to operate that technology?

Smart Home Technology Diffusion

Much of the literature surrounding smart home technology focuses on either elderly populations or energy consumption. While these are worthy considerations, little research has been devoted to how smart home technology is actually used and adopted by residents in their own homes. Furthermore, almost no research has focused on what residents provided with smart home technology choose to do with it or how they learn about those products. As Hargreaves, Wilson, and Hauxwell-Baldwin (2018) point out, most research on smart home technology has been focused on the technical aspects of that technology, while users have been widely ignored. Meanwhile, other research suggests that “smart home providers should survey user needs for their product instead of merely producing smart homes based on the design of the builder or engineer” (Luor, Lu, Yu, & Lu, 2015, p. 377). These observations, coupled with the fact that smart home technology adoption has been generally low, paint a murky picture of smart home technology users.

As Brush et al. (2011) shows, smart home technologies have been available for over 30 years yet have not been widely adopted. Brush’s research utilized homes with existing technology, and points to four primary reasons for lackluster sales: high cost of ownership, inflexibility, poor manageability, and poor security. Security and data privacy have arguably become one of the biggest issues for smart home products since the time of Brush’s study with news reports of companies surreptitiously recording conversations, house layouts, and personal information. Shank, Graves, Gott, Gamez, and Rodriguez (2019) have shown that people often report strong emotional responses of fear and unease from situations where supposedly dormant smart home and personal assistants appear to be recording, monitoring, and responding to conversations.

The pattern of high cost, inflexibility, poor management, and security/privacy issues (Brush, 2011) is not dissimilar to other electronic technologies. As Cortada (2013) shows, information technologies, including computers, were not widely adopted until they became less expensive and easier to use than their early counterparts. However, marketing and product support were also both major influences on the spread of computers and information technology (IT; Cortada, 2013). He says, in speaking of IT proliferation,

The two principal actions of suppliers making this possible were the introduction of commercially viable products into markets, and the methods of marketing they brought to bear on potential customers, motivating them to acquire a technology now that might just as easily be appropriated at a later time or else not at all. (p. 240)

In addition, large IT manufacturers were able to provide training and technical support to potential users who might not otherwise have realized how IT could help them accomplish their goals.

The same has not been true for smart home technology manufacturers, for several reasons. First, IT marketers were able to connect their technology directly to work productivity. This was pivotal in creating large-scale investment from corporations. While smart home technology marketers might connect their users’ desire for productivity with saving time, the monetary concerns that exist in industry simply do not exist for the average home resident.

In fact, even “smart” technologies that have been implemented in industrial and corporate settings have been largely focused on energy saving measures. On the contrary, when studying home residents, Haines, Mitchell, Cooper, and Maguire (2007) found that individuals value people, space, and memories more highly than technology or possessions and that smart home technology was most highly valued for its ability to provide comfort and relaxation. Therefore, corporate adopters and individual adopters are inherently different in their approach to smart home technology. However, according to Hargreaves and Wilson’s (2017) study, 86% of survey respondents agreed that smart home technology is primarily designed to control energy, heating, and appliances. This would appear to be in direct contrast to the comfort and relaxation features most prized by home residents and must account for at least some of smart home technology’s failure to proliferate.

Users want control over their home environment and products that are “designed to be reliable, easy to use, controllable, and easy to over-ride” (Hargreaves & Wilson, 2017, p. 43). At the same time, users want technology to be secure and automation that does not make them overly dependent. Mennicken and Huang (2012) show that users are not necessarily awed by technology itself or the “gadgety” features of smart home technology. Instead, most take a more practical approach, saying that they “do not see a benefit to automation if they could still perform the same task faster or better manually” (p. 150). In addition, in later research, Mennicken et al. (2016) show that users, “do not want their home to be an unknown person with a mind of its own, but rather an intelligent helper that supports them to complete everyday tasks better or quicker while knowing when to leave inhabitants alone” (pp. 128–129).

In a massive survey, Balta-Ozkan, Davidson, Bicket, and Whitmarsh (2013) gathered information from the existing literature, the general public, and smart home technology “experts.” In doing so, they found a disconnect between the concerns cited in the literature and by experts versus those raised by the general public. While the existing literature and experts identified (p. 371)

fit to current lifestyles,

technological complexity,

interoperability and standards,

reliability, and

privacy and security

as chief concerns for designing smart home technology, the general public identified (Balta-Ozkan et al., 2013, p. 371)

loss of control and apathy;

poor reliability;

viewing smart home technology as divisive, exclusive, or irrelevant;

privacy and data security;

cost; and

trust

as primary concerns. Thus, the barriers to proliferation among users are more closely related to lifestyle concerns rather than to technological concerns. The authors are careful to point out that this discrepancy does not preclude proliferation of smart home technology, saying, “Rather, as articulated by experts, consumer acceptance is dependent on their having a clear sense of smart home benefits; but the relatively limited financial savings they can provide is not enough of a strong drive on its own” (Balta-Ozkan et al., 2013, p. 372).

Hargreaves et al. (2018) agree, saying that there is little evidence to support the notion that smart homes will provide substantial energy saving for residents. Furthermore, their extended, in-home research points to complex learning demands placed on users as a strong detriment to utilizing smart home technology. There is little support for users at this time, and the authors found that “there was little interest in this group in making use of the more advanced and automated features of the systems” (Hargreaves et al., 2018, p. 134). Thus, it stands to reason that users will require much more extensive support from manufacturers if they are to navigate the more intricate features of smart home technology. As Hargreaves et al. (2014) say,

The result is that current visions of smart homes have a limited appeal to users and are perceived as failing to meet user needs. This has given rise to what Nyborg and Røpke term “funwashing” as smart home developers seek to broaden the appeal of smart homes because the basic functionality they offer has not proven as attractive as initially hoped. (p. 473)

Instead, the authors recommend,

systems that allow users to communicate with SHTs [Smart Home Technologies] in ways that make sense to users themselves, rather than having to learn complex technical languages and commands, and technologies that can make suggestions about how they might be used and the impacts they might have. (p. 128)

Some authors have offered definitive areas for interpreting smart home technology apart from the theoretical constructs mentioned previously. Wilson, Hargreaves, and Hauxwell-Baldwin (2015) speak of a functional narrative (what can be controlled), an instrumental narrative (user-tech interaction), and a sociotechnical narrative (the relationship between technology and society). These are important and useful classifications. However, as Wilson, Hargreaves, and Hauxwell-Baldwin (2017) say,

Analysis of reports, studies, websites and promotional material produced by smart home technology developers and service providers reveals a notable absence of user-focused research. User-oriented studies in actual smart home environments are notable exceptions rather than the rule (15).

This study is one step in correcting that absence.

Theoretical Perspectives on Innovation Diffusion

The Classic Diffusion Model

Rogers’ (1995) Diffusion of Innovations is generally viewed as the classic treatise on diffusion. Rogers views innovation adoption as a social process, but one that relies heavily upon individuals’ ability to reduce uncertainty about the innovation in question. Rogers’ model shows that, when faced with decisions about new technologies, people go through a process that attempts to gather information and reduce risk. Through information seeking, potential users reduce uncertainty about an innovation’s capacity to provide personal advantages and disadvantages. But Rogers and others associated with the classic diffusion model (Coleman, Katz, & Menzel, 1966; Katz, Levin & Hamilton, 1963; Rogers & Kincaid, 1981) also realized that adoptions are largely social and that interpersonal communication networks play a large part in shaping users’ attitudes toward innovations. In essence, the technological innovations that offer “obvious benefits” rarely proliferate solely on the basis of those benefits. Communication and interaction must accompany innovations to reduce uncertainty among would-be adopters.

The Cultural Diffusion Model

Because diffusion is a social process, culture plays a primary role in adoption. The cultural model, developed largely through the work of sociologists and anthropologists, emphasizes societal values and social structure as diffusion determinants (Katz, Levin, & Hamilton, 1963). In addition, cultural diffusion is identified by the fact that certain biases and technological preferences may be “inherited” as a person becomes a member of a specific culture. In other words, as we grow and mature as part of our own culture, we inherit core beliefs and attitudes (Tindall, 1976) about the technologies that are part of that culture (Batteau, 2010).

In many ways, the cultural model is an addition to the classic model. However, researchers point out that cultural factors affecting diffusion are often biased and that those biases can often be more influential than risk/reward models allow (Heinrich, 2001). In addition, some research shows that cultural learning has a stronger impact on technology adoption than individual factors (Cavilli-Sforza & Feldman, 1981; Mesoudi & O’Brien, 2008).

The Knowledge Barrier Model (Organizational Model)

As innovations become more complex, our ability to understand them diminishes, as we become further removed from the specialized knowledge used to create those innovations. This distance reduces our ability to transfer technology individually and creates the aforementioned “knowledge barrier.” While early studies of diffusion saw adoption as a single event, later authors (Attewell, 1992) began to see diffusion as an increasingly large-scale event driven by organizational adoption. The theory claims that innovations must be “framed” in beneficial ways before organizations will adopt them (Barret, Heracleous, & Walsham, 2013). Internal experts, external proponents, consultants, professional societies, and in-house training are more important than individuals from this viewpoint, and organizational learning takes priority over individual learning.

Technology Acceptance Model and Later Theories

While it may be possible to place technology acceptance model (TAM) within the categories described earlier, its original theory (Davis, 1989; Davis, Bagozzi, & Warshaw, 1989) and its successor TAM2 (Venkatesh & Davis, 2000) have both received widespread attention and use. The original theory proposes two variables, perceived ease of use and perceived usefulness, as fundamental to technology diffusion. TAM2 incorporates social influences and cognitive processes into the original theory. Finally, Venkatesh, Morris, Davis, and Davis (2003) attempted to incorporate those two theories with other leading technology diffusion theories by developing the unified theory of acceptance and use of technology (UTAUT). That theory posits that performance expectancy, effort expectancy, social influence, and facilitating conditions all impact technology diffusion.

Making Sense of the Theories

It would be impossible to list all theories of diffusion here or to even give extended treatment to the theories listed. While the perspectives listed earlier all have their own strengths, each has also been criticized. For example, Rogers’ diffusion theory has been criticized for being difficult to update and to apply to new problems. The knowledge barrier model was originally conceived as a tool for predicting organizational adoption and is therefore considered by many to be unsuited for individual adoption studies. The cultural diffusion model can be criticized as overly reliant on knowledge that has been passed on culturally, thereby ignoring individual decision-making. TAM has been criticized for being overly simplistic and having little predictive value, and TAM2 has also been criticized for its lack of predictive value. Finally, even UTAUT, which has shown more predictive value than its counterparts, has been criticized for being overly complex (Bagozzi, 2007) and for its lack of actual use given its numerous citations (Williams, Rana, Dwivedi, & Lal, 2011). Indeed, given the complexity of current technologies and the complex nature of human adoption, it would be hard for any one theory to completely capture all variables involved.

In addition, while theories such as these provide a lens through which adoption can be viewed, they do not in and of themselves provide a systematic methodology. However, they are useful in terms of discussing research data and we use them in this way. We return to the question of which theory is supported in the discussion.

Methods

For our purposes, we made investigative choices based on the pragmatic research paradigm, which prizes the research problem as the central focus and promotes, “methods most likely to provide insights into the question with no philosophical loyalty to any alternative paradigm” (Mackenzie & Knipe, 2006, p. 1). In doing so, we chose a mixed-methods approach that is well suited to gaining information about real-world problems (see Creswell, 2003; Creswell & Creswell, 2017; Johnson & Onwuegbuzie, 2004). We conducted a series of surveys from September 2017 through April 2018, with both quantitative and qualitative questions included in the surveys, in order to gain a more robust picture of life with the installed technology. In this article, we primarily discuss the qualitative responses and key trends supported by both the qualitative and quantitative responses.

To study smart home technology in real living environments, we first needed to secure residences and provide residents with smart home technology. Fortunately, the Missouri University of Science and Technology Solar Village (Figure 1) offers an ideal environment to conduct living laboratory studies of this nature.

Figure 1.

Solar village houses. Missouri S&T Solar Village.

Missouri University of Science and Technology students began competing in the Solar Decathlon in 2000, designing homes to be powered by solar energy. Student design teams have built homes for competition since, and after the competitions, the houses have been returned to the campus for student use as living quarters. Students request to live in the houses, which are their primary residences while attending school and are offered discounted living expenses in exchange for agreeing to participate in research projects, usually involving power use. Therefore, student participants were neither recruited for this research specifically nor requested this technology. This is important, as it provides a unique situation to study smart home technology diffusion among people who did not actively seek out the smart home devices.

There were a total of nine residents in the five houses. The initial survey, conducted in August 2017, revealed that residents were from various backgrounds, genders, and ethnicities, but all were university students between the ages of 21 and 27 years. Residents had lived in their respective houses from 1 week to 10 months. There were two biological science majors, one computer science major, and six engineering majors. In addition, all had experience with modern technology including cell phones, computers, and wireless internet use.

The Smart Home Devices and Possibilities for Their Use

The five houses were initially outfitted with smart home technology including the following devices (see Appendix A for technology by house). While all houses had most of these technologies, there were some differences in the number of devices and their setup due to building design differences. For example, not all houses were capable of supporting tunable light bulbs.

GE Z-Wave In-Wall Dimmer

GE Z-Wave Smart Outlets

Honeywell Wi-Fi Thermostat

Schlage Connect Deadbolt

Ring Video Doorbell

Samsung Multipurpose Sensors

Samsung Motion Sensors

Samsung SmartThings Hub

Netgear Nighthawk AC1900 Smart Router

Eufy Smart Bulbs (White)

Eufy Smart Bulbs (Tunable)

Amazon Echo

Amazon Echo Dot

Most devices are capable of being controlled through voice commands (Amazon Echo), through installed cell phone apps, or manually. Therefore, residents could conceivably control many house functions either from within the house or remotely through cell phone apps. Common practices might include turning on, off, or dimming lights; turning on or off devices plugged into outlets; controlling the thermostat; and locking or unlocking doors.

In addition, more complex functions can be programmed through the smart hub. For example, an alert can be sent by the multipurpose sensor to a cell phone if a door or window is unexpectedly opened. The same sensor is capable of automatically adjusting the thermostat in response to changes in temperature or humidity. Live video can be sent to a cell phone when the doorbell rings. Doors can be programmed to automatically lock at certain times or in response to stimuli and can be opened or locked from virtually anywhere. Motion sensors can be programmed to turn on individual lights or multiple lights in response to motion and can be set to do so at certain times if desired (e.g., only at night).

Certain “scenes” can also be created to control multiple devices easily. For example, a resident might create a scene that would respond to a voice command through Amazon’s Alexa. The phrase, “Alexa I’m home” might cause the front door to lock, the thermostat to adjust to 70 degrees, a television to turn on to a favorite channel or music station, a coffee pot to begin brewing, and lights to be set to 50% illumination. This is all possible by linking Alexa with the smart home hub, which in turn controls the various bulbs, dimmers, devices, and outlets that make up part of the scene.

The phrase, “Alexa, movie time” might cause lighting to change to purple, for example, and Netflix to open on the television. In reality, there are myriads of possible combinations of devices, outlets, light bulbs, dimmers, and devises that can be combined to create environments like those commonly seen in advertisements for these technologies. One of our guiding questions was would residents use them for these purposes?

Overview of Survey Process

Residents were given a brief overview of the technology installed in their homes and links to further information about each device and the cell phone apps that could be used to control them. However, because one of our research goals was to discover how residents learn about and apply smart home technology, further instructions on how to set up complex “scenes” and otherwise manipulate devices were not provided.

Researchers held one meeting with residents to familiarize them with the study and with the technology in their homes. At that time, they were also given an informational flyer detailing sources for further information (Appendix B). After that meeting, residents were each asked to complete an initial survey designed to determine their experience level with each installed device and initial opinions of the devices. Following the initial survey, residents were asked to complete five data collection surveys during the following 8 months (Appendix C).

For each ongoing survey, residents were asked to rate their use of and attitude toward each device. Residents were then asked to rate each device on the basis of usability and lifestyle comfort. Next, residents were asked to rate the aspects of their life that would be important when choosing smart home devices and about how they had chosen to learn about the devices. Finally, residents were asked to leave comments about each device, to rate cost barriers to purchasing such a device, and given an opportunity to further explain their interactions with the devices.

Results

Initial Survey

The initial survey revealed that residents had some experience with the smart home devices, although no more than one resident (of nine) reported actually living with any single device other than the Amazon Echo or Dot.

Residents were then asked to rate their initial experience with and attitude toward each device.

The following devices were listed for rating:

Power Monitoring Device

Environmental Sensors (temperature, humidity, and open doors)

Smart Home Hub Controller

Amazon Echo

Smart Outlets

Motion Sensors

Smart Door Locks

Smart Thermostat

Smart Switches for Lights

Video Doorbell

Overall, initial impressions of smart home technology were quite high. Residents reported that they expected the devices to be fairly easy to use, innovative, and positive, and all residents indicated that they believed every device to be at least somewhat useful. All residents also reported that they were early adopters of technology and that they expected to use all of the devices to some extent, although on average the smart thermostats, door locks, Amazon Echo, and motion sensors received the highest anticipated use rankings.

The initial survey also asked residents to rate the importance of the following lifestyle parameters identified by previous research (Brush et al., 2011; Mennicken & Huang, 2012; Oliveira et al., 2015), and each device’s ability to impact those parameters.

Make your life easier

Save you money

Save you time

Be fun to use

Make you feel safer

Make you feel in control

Make you feel technologically advanced

Make your home feel modern

Reduce your environmental impact

Results show that users rated making their lives easier, saving time, being fun to use, and making their home feel modern as the most important lifestyle factors. But the results also show that none of the installed devices averaged particularly highly in those categories on the initial survey. So, although residents ranked devices positively, believed them to be both innovative and easy to use, and planned to use them, they were not initially convinced that the products would improve their lifestyle significantly. Residents were then asked to rate themselves as adopters of technology and as technological investigators. Results show that most residents rated themselves as both early adopters of technology and as technologically savvy.

Ongoing Surveys

After the initial survey, residents were given the ongoing survey a total of five times during the following 8 months (September 2017–April 2018). Surveys were sent to residents approximately every 6 weeks. In addition to the lifestyle ratings earlier, residents were asked to provide an additional set of usability ratings for each device (see Appendix C). The means and standard deviations were computed using Microsoft Excel and of each of these key measures by smart home product type are presented in Table D1.

Table 1.

Number of Times Residents Learned More About Their Smart Home Devices.

Source	Number of times reported (over 8 months)
Information PDF and its links that we provided you	2
Talking with anyone on this project or part of the solar house oversight	1
Discussions with housemates	4
Discussions with friends	3
Discussions with technical support	0
Discussions over the Internet with people you do not know personally	0
Manuals from the company who created the smart product	0
Other information sources such as manuals or websites	2
General Internet searches	3
Trial and error	4

Note. Attempts to learn about smart home devices.

Most devices received fairly consistent ratings on both attitude ratings and usability ratings, with most metrics hovering between 4.0 and 6.0 (Scale 1–7). However, lifestyle ratings were considerably lower, as residents evidently did not see the devices as an integral part of improving their lifestyles. In fact, of the lifestyle rankings, the only categories that averaged over 50% positive resident ratings were as follows: “Make you feel technologically advanced” and “Make your home feel modern.” Over time, ratings for devices being able to “save money,” “save time,” and being “fun to use” remained stable or declined.

Finally, residents were also asked if they had undertaken any activities to learn about their devices and how many times they had done so (Table 1).

Clearly, despite their relatively high rankings of devices on usability and attitude measures, residents spent little time beyond casual discussions with housemates or trial and error in learning about the devices. Few residents even bothered to read the informational handout that they were given during our original meeting.

Comments on Individual Devices

Residents were also asked to provide comments on individual devices throughout the survey process. We initially examined these qualitative data a number of ways; we organized it by participant, by device, and by survey time point. Examining the data each of these ways showed no meaningful patterns by participants or survey time but clear patterns of differences by device. Table 2 shows selected comments from this organization, edited for repetitive comments by the same participants. Later, we summarize the major findings from analyzing this open-ended data.

Table 2.

Selected Comments On Individual Devices.

Device	Comments
Power Monitoring Device	I don’t look at this much, but it is interesting to look at it here and there I am not sure how to use this or if we have one. I assume it is in the SmartThings app, which I do not utilize We do not know how to use this
Multipurpose Sensors (temperature, humidity, and open doors)	I don’t think these works or don’t know how to access the data. We don’t know how to use this I’m not sure if these are hooked up
Smart Home Hub Controller	I don’t know what this is but I assume it is something that links our house and all of the smart devices together, or something like that I’m not sure if this is installed yet
Amazon Echo	I like the amazon echo, but over the last year, I have found myself to use it for two things: a timer and for playing music, and that is all. I have not put much effort into using it for other things, but it does not seem extremely useful as I would much rather order pizza myself to change the order, or look at a clock, or look online for weather, etc. I almost see it as more of a gimmick and fun to use when you do I mentioned before that I think it is more of a gimmick than anything, and I still think that to an extent. I realize now that a lot of the things you can do with it we have not set up or are not able to set up (such as light settings since our house has uncommon light switches). I still do not use it for things other than setting timers, alarms, playing music, weather, and time “I’ve found that it is pretty useful while doing homework. I can be working on a computer screen or paper off of the computer and ask it simple questions like” (what is the molar mass of ammonium hydroxide) I am not a fan of the Amazon Alexa to be honest. The only thing I use it for is a timer and maybe weather and maybe from time to time music. This device regularly hears things wrong and interprets things wrong. Not my thing when I have a smart phone which can do all the same stuff with less effort most of the time I unplugged mine since I did not use it for anything other than music and timers. It was getting annoying with how it does not understand anything you say or ask of it and it always says HELLOOO when it reboots due to the house power regularly restarting. More or less: it is useless to me, I initially like it but it definitely died on me over time. Maybe I could have hooked it up to more stuff, but the stuff that it can hook up to do not really help me in much way, just to be more lazy
Smart Outlets	I am not sure of what these are, or what they do. I also don’t think we have them installed in our house, or are even getting them installed I’d like to use this more, but don’t have many plugged in electronics that I’d like to use with it. I have a personal remote control for the one lamp that I have automated They are a little hard to get used to since you must use either the appliance’s switch or a smart device. It can be inconvenient if you want to use them interchangeably
Motion Sensors	Don’t understand them or where they are or why they need to see I’m there I don’t understand what the purpose of these are yet. Are they for security reasons? Are they for turning lights on? I dislike these and prefer to manage lights and other utilities manually or via a central hub I don’t like these and don’t plan to use them
Smart Door Locks	I like these locks, just need to not forget my code after I have been gone for 4 weeks with the solar house trip. That could be an issue with these locks, since I did not personally set up the lock to be something that I would more easily remember The smart lock is a very nice device that is simple to use The keypad is pretty reliable, but Alexa cannot always access it properly when asked to, despite recognizing the command This is great This is really the only super useful one
Smart Thermostat	I like this new thermostat which was implemented, it can do a lot more things than the old generic one This is good device I like this item. I did not set up the online controlling (through your phone), but that is still available to set up for the next tenant. I think this thing can really help people out to save money and energy, especially with the daily schedule setup
Smart Switches for Lights	These devices are unresponsive, but earlier in the semester they worked nicely I just can’t see not turning on a light myself
Video Doorbell	I haven’t used this I don’t use a smart phone I do like the idea and it definitely makes the house feel safer I do like the ring doorbell and how it makes the houses safer I like these a lot, and they fit in with the houses. I do not think that any of the houses have any of these though. I think that it would be beneficial as a security thing to have these on the houses though

Note. User comments on individual devices.

The most common comments concerning installed technology were as follows: “I’m not aware of this,” I haven’t used/don’t know how to use this,” and “I don’t know what this is.” Despite residents’ mostly favorable initial attitudes toward the devices, their comments over time are mostly negative.

For example, one resident called the power monitoring system, “the dumbest thing in the house” while another resident referred to the Amazon Alexa as “more or less useless” and another said that he had “referenced this online and then just unplugged it.” As for the motion sensors and multipurpose sensors, residents’ comments typically showed that they either did not know where they were or, as one resident put it, “I’m not sure why these need to know that I’m here.” In general, the residents made no connection between these devices and the more complex functions that they could have performed in combination with other devices, instead looking on them as singular devices without connection to the others.

There were more positive comments about some devices. The smart door locks, doorbells, and thermostats in particular received favorable comments from some residents. Some residents found these devices easy to use and enjoyed their basic functions. Again, however, residents did not move beyond basic features such as using a code to unlock the door or setting a timer on the thermostat. Table 2 shows comments by individual device.

Perhaps one of the most telling comments from the surveys read as follows,

I do not think that I would purchase many of the technologies with my own money since I do not have much to spend on things such as these which I can obviously live without (have lived here for a year already without them and at my childhood house without them forever), but if they are provided then we can try to use them and see how we like them.

Residents were provided with that technology and did have a chance to see how they liked the devices. In the end, they did little with them and made less effort to learn about their more complex capabilities.

Discussion

Smart home technology has been promoted as the way of the future by manufacturers and has also been marketed as easy to install and use by common citizens. However, as Brush (2011) shows, high cost of ownership, inflexibility, poor manageability, and poor security have traditionally blocked smart home technologies from widespread diffusion. In addition, research shows that consumers want control, reliability, security (Hargreaves & Wilson, 2017), functionality as opposed to gadgetry (Mennicken & Huang, 2012), and that consumers see no benefits to automated tasks that can be easily performed manually.

However, as stated earlier, most smart home products are not accompanied by detailed instructions beyond initial setup. Furthermore, while residents were provided with an informational handout that explained the technology installed and where to find more detailed information, few of them took the time to investigate that information. This is an important technical communication finding and might be attributed to several factors. First, the informational handout did not provide detailed instructions for using the more complex features of the technology. It merely described the technology and provided links to further information about that technology. Therefore, it is possible that residents, upon seeing that the handout did not provide detailed instructions, dismissed it as a further complication. Second, as early adopters of technology such as cell phones and gaming systems, residents may have assumed that they could “work it out” on their own. When that proved to be more difficult than expected, they may have abandoned the effort.

Taken in this light, this set of data begins to make sense. It is perhaps most interesting to note that while residents were rating the technology quite highly in terms of its capability they made little effort to learn about the technology and their comments reveal why. Without the training required to make using the devices simple, the residents did not believe that the potential benefits were worth the required time investment. This has important implications for both technical communicators and manufacturers of smart home technology. For example, if Amazon and Google want their devices to be the centerpiece of a voice-controlled smart home environment, then it seems reasonable to expect those devices to help with installation as well. If Alexa can tell me what the weather is in any given location, for example, why could it not tell me how to link my Samsung Multipurpose Sensor to my smart home hub and to other installed devices? Better still, if it is already linked to my Fire TV Cube, why not link directly to a video with detailed instructions and an explanation of benefits?

Whatever possibilities exist, it seems clear that technical communicators and manufacturers will need to provide more detailed instructions and benefit explanations, and through multiple delivery methods, if they wish smart home devices to become more widely accepted and utilized. If for no other reason, this would help with compatibility issues that still exist between devices manufactured by different companies. Several comments from out study mention devices not working properly, which was at times an issue during the study and was often due to compatibility issues or unique structural issues. As an example, when we first installed the smart locks in our houses, we realized that commanding Alexa to “unlock the door” was unlocking every door in the village. Only after extensive investigation did we realize that because every house was connected to the same wireless network, all of our commands were circulating throughout the neighborhood. This typifies the setup issues that many new users of smart home devices encounter, and those issues will need to be resolved via communication products before the technology proliferates.

Still, in our study, it was far more common for residents to be unaware of the technology than for it to be inoperable or for them to be either uninterested in or distrustful of the technology. In many cases, devices such as motion sensors and multipurpose sensors were simply ignored. Later, in their comments, residents would say, “I don’t know what this is” or “I don’t know how this works,” while simultaneously revealing that they had made little effort to discover the answers to those questions.

So, in response to the two questions we originally sought to answer,

How likely are residents to adopt smart home technology when they are provided with that technology but not provided with training to accompany it?

How do residents provided with smart home technology learn to operate that technology?

We must conclude from these data that the residents did not adopt the majority of installed technology and made little effort to learn about it. We attribute this primarily to three things. First, smart home technology is still difficult to program and control. In determining whether to invest the time and energy necessary to learn programming and control (a risk), residents reported that the added lifestyle enhancements would be of suitable benefit. Second, because residents were given the technology without support for learning to operate that technology, they were unlikely to understand the technology and unlikely to grasp the full range of possible benefits. This is not unlike the findings reported by Jakobi, Ogonowski, Castelli, Stevens, and Wulf (2017) in saying,

When households were picking components for setting up their future smart home, it became obvious that many had very little knowledge of the various features of sensors and actors, as well as of their potential for combination. (p. 1625)

Third, the technical capabilities that were reported to be understood by residents were underwhelming and represented only minimal lifestyle enhancements for them.

When viewed through the lens of the theoretical constructs discussed earlier, our smart home technology failed to be adopted for several reasons. As mentioned previously, technological innovations that offer “obvious benefits” rarely proliferate solely on the basis of those benefits. The classic diffusion model posits that communication and interaction must accompany innovations to reduce uncertainty among would-be adopters (Rogers, 1995). In designing this study, we intentionally avoided providing training to support these devices beyond what students could locate themselves. Doing so meant that the smart home technologies would need to be adopted on the basis of their potential, rather than expanded knowledge of the devices. Evidently, this was not enough to promote adoption. This may offer some explanation for the technology’s low adoption rate among the general public, as there has been little support offered by manufacturers to date.

Nor was the cultural inclination of our residents (who largely purport to be early adopters of technology) enough to motivate personal investigation beyond casual conversation and occasional trial and error. Furthermore, if we view the data from the perspective of the knowledge barrier model, it would seem that the knowledge gap between these complex innovations and residents was more than they were willing to overcome through investigation. And finally, from the perspective of TAM, TAM2, and UTAUT, we can say that perceived ease of use did not measure up to perceived usefulness, that social factors played little part in mediating that discrepancy, and that effort expectancy exceeded performance expectancy.

However, their comments do show that they did not understand the technology and that they considered the technology capable of only minimal lifestyle enhancement. In their study, Hargreaves et al. (2018) found that “there was little interest in this group in making use of the more advanced and automated features of the systems” (p. 134) and we must conclude the same.

Although usability and attitude measures remained basically static or rose over time, lifestyle measures started and remained low. Given the fact that lifestyle indicators were clearly the most important measure to residents, it seems likely that the subjects simply never bothered to learn enough about the devices to greatly affect their opinions. Rather than spend the time required to learn about the more complex features of the devices, they simply ignored them, preferring instead to gain what they could from easier, more basic features.

Future Research and Limitations of This Study

The unique nature of the solar village limited the number of participants in this study. Also, we were unable to conduct interviews or focus groups with participants, which would have yielded advantages for this sample size including eliciting more specific details than the open-ended questions provided in the surveys. Those limitations resulted in what might be called a quasi-mixed methods approach. We have arranged to add both interviews and focus groups to future research at the site.

The site, however, did offer a unique opportunity to install smart home technology for residents who have not asked for it. This gives our research an advantage in terms of understanding people’s interaction with smart home technology without selecting primarily early adopters or those with a prior history as participants. But, in the future, we hope to also actively recruit residents who proclaim an interest in using complex smart home features before being given the technology, rather than after. It would be interesting to see whether that attitude with or without training would make a difference in resident use of the technology.

It is also important to remember that the participants in this study were young and healthy. Studies concerning the older adults or disabled might, and in some cases, have found much different results (see Demiris et al., 2004; Morris et al., 2013; Pal, Funilkul, Vanijja, & Papasratorn, 2018; Portet, Vacher, Golanski, Roux, & Meillon, 2013). In addition, as smart home technology becomes increasingly easier to use and deploy, specifically when artificial intelligence may reach a level that allows for more collaboration between residents and systems, we may see a marked change.

At the conclusion of these data collection cycle, most residents moved out of the village. Prior to the start of the next data collection cycle in the solar village, we plan to conduct extensive training with the incoming residents when they move into the village. We also plan to conduct another training session at the midpoint of the data collection process and to hold troubleshooting meetings for residents periodically. It remains to be seen whether being given the knowledge to operate smart home technology will be a greater incentive than simply being given the technology.

Appendix A: Smart Home Technology

All Devices

GE Z-Wave In-Wall Dimmer

GE Z-Wave Smart Outlet

Honeywell Wi-Fi Thermostat

Schlage Connect Deadbolt

Ring Video Doorbell

Samsung Multi Sensors

Samsung Motion Sensor

Samsung SmartThings Hub

Netgear Nighthawk AC1900 Smart Router

Curb Energy Monitoring System

Lutron Caseta Smart Bridge

Lutron Caseta Smart Dimmer

Lutron Caseta Pico Remote

Wink 2 Smart Hub

Eufy Smart Bulb (White)

Eufy Smart Bulb (Tunable)

Amazon Echo

Amazon Echo Dot

Amazon Fire TV Cube

Philips Hue Smart Bulb

Samsung 43″ Smart Hub TV

2002 House

6 GE Z-Wave Dimmers

8 GE Z-Wave Smart Outlets

1 Schlage Connect Doorbell

1 Ring Video Doorbell

1 Samsung Multi Sensor

1 Samsung SmartThings Hub

1 Amazon Echo

1 Amazon Echo Dot

1 Netgear Nighthawk AC1900 Smart Router

2005 House

7 GE Z-Wave Dimmers

9 GE Z-Wave Smart Outlets

1 Schlage Connect Doorbell

1 Ring Video Doorbell

1 Samsung Multi Sensor

1 Samsung Motion Sensor

1 Samsung SmartThings Hub

1 Amazon Echo

1 Amazon Echo Dot

1 Netgear Nighthawk AC1900 Smart Router

2007 House

8 GE Z-Wave Dimmers

11 GE Z-Wave Smart Outlets

1 Schlage Connect Doorbell

1 Ring Video Doorbell

1 Samsung Multi Sensor

1 Samsung Motion Sensor

1 Samsung SmartThings Hub

1 Amazon Echo

1 Amazon Echo Dot

1 Netgear Nighthawk AC1900 Smart Router

2 Curb Energy Monitoring Systems

2009 House

6 GE Z-Wave Smart Outlets

1 Schlage Connect Doorbell

1 Ring Video Doorbell

1 Samsung Multi Sensor

1 Samsung SmartThings Hub

1 Amazon Echo

1 Amazon Echo Dot

Appendix B: Orientation for Residents ( double-click image for complete file )

Appendix C: Data Collection Survey

Solar Village Ongoing Survey

This research study is to find out how people use, adapt, think about, and change their behavior in response to living in a house with smart home technology.

Q7 Rate each device based on where you think it best fits between each phrase set.

	(0)	(1)	(2)	(3)	(4)	(5)	(6)
I have never used one (1)	○	○	○	○	○	○	○	I often use one
I plan to not use this at all over the next month (2)	○	○	○	○	○	○	○	I plan to use this often over the next month
I am uncertain of its usefulness (3)	○	○	○	○	○	○	○	I am certain of its usefulness
It seems difficult to use (4)	○	○	○	○	○	○	○	It seems easy to use
It is not innovative (5)	○	○	○	○	○	○	○	It is innovative
I feel negative about it (6)	○	○	○	○	○	○	○	I feel positive about it
It does not involve sensitive data (7)	○	○	○	○	○	○	○	It involves sensitive data
I do not know anyone who has one (8)	○	○	○	○	○	○	○	I know many people who have one

Rate each device based on where you think it best fits between each phrase set.

	(0)	(1)	(2)	(3)	(4)	(5)	(6)
It is not beneficial to me (1)	○	○	○	○	○	○	○	It is beneficial to me
It is safe to use (2)	○	○	○	○	○	○	○	It is not safe to use
I do not understand it well (3)	○	○	○	○	○	○	○	I do understand it well
It is unreliable/unpredictable (4)	○	○	○	○	○	○	○	It is reliable/predictable
It is difficult for visitors to use (5)	○	○	○	○	○	○	○	It is easy for visitors to use
It is a privacy concern (6)	○	○	○	○	○	○	○	It is not a privacy concern
It does not work well with other technology (7)	○	○	○	○	○	○	○	It does work well with other technology
It does not fit well with my home (8)	○	○	○	○	○	○	○	It does fit well with my home

In which ways would each device be beneficial to you? (Mark all that apply)

□ Make your life easier (1)

□ Save you money (2)

□ Save you time (3)

□ Be fun to use (4)

□ Make you feel safer (5)

□ Make you feel in control (6)

□ Make you feel technologically advanced (9)

□ Make your home feel modern (7)

□ Reduce your environmental impact (13)

□ Other; please specify (11) _______________________________________

Please add any additional comments you have about this device.

________________________________________________________________

End of Block: Smart Product Rating

Start of Block: End Questions

Q11 Thank you for rating those. Now, we would like to ask you a few general questions pertaining to all the devices you have seen in this survey.

Q12 How much do you agree with the following statement: If I had to purchase these smart products on my own, the cost of them would likely be a major obstacle.

○ Strongly agree (4)

○ Agree (5)

○ Somewhat agree (6)

○ Neither agree nor disagree (7)

○ Somewhat disagree (8)

○ Disagree (9)

○ Strongly disagree (10)

How important are each of these to you in regard to setting up your home? (Mark all that apply)

□ Make your life easier (1)

□ Save you money (2)

□ Save you time (3)

□ Be fun to use (4)

□ Make you feel safer (5)

□ Make you feel in control (6)

□ Make you feel technologically advanced (9)

□ Make your home feel modern (7)

□ Reduce your environmental impact (13)

□ Other; please specify (11) ________________________________________

What technologies and devices have you added to your solar house since the last survey? Please list if any.

________________________________________________________________

Since the last survey, have you use any of the following to learn about any of the smart home products in your house? (Mark all that apply)

□ Information PDF and its links that we provided you (1)

□ Talking with anyone on this project or part of the solar house oversight (5)

□ Discussions with housemates (6)

□ Discussions with friends (7)

□ Discussions with technical support (8)

□ Discussions over the Internet with people you do not know personally (9)

□ Manuals from the company who created the smart product (10)

□ Other information sources such as manuals or websites (11)

□ General Internet searches (12)

□ Trial and error (13)

□ Other (please specify) (14) ________________________________________

Were you satisfied with the information you found?

○ Not at all (1)

○ A little (2)

○ A lot (3)

○ Completely (16)

Did you enable, disable, or move around any of the smart home products this month? If so, please explain.

________________________________________________________________

Did you connect any of the smart home products to each other or to other technologies in the last month? If so, please specify which ones and explain what you did and why.

________________________________________________________________

Did you or others add any new technology to your house or change any of the existing technology? This could be repairs, additions for a specific purpose like a box fan for summer or just new purchases like an Xbox. Tell us the any additional information about what happened or why it was added.

________________________________________________________________

What new smart home products or technologies would you like to be added to your house? Why would they be useful?

________________________________________________________________

Who are the other people who come to your house and how do they use the smart home products if at all (do not mention names, but refer to people by roles such as friends, classmates, relatives, or significant others)?

________________________________________________________________

Thank you for taking part in this study!

If you have feedback or encountered any problems, please let us know here:

________________________________________________________________

Appendix D

Table D1. Mean and Standard Deviation of Primary Measures by Each Smart Home devices.

	Power Monitoring Device	Environmental Sensors	Hub Controller	Amazon Echo	Smart Outlets	Motion Sensors	Smart Door Locks	Smart Thermostat	Smart Light Switches	Video Doorbell	Total (all products)
N	34	34	34	34	34	34	34	34	26	26	324
Use
Previous experience	2.16 (1.48)	2.36 (1.75)	3.34 (2.03)	4.47 (1.92)	4.27 (2.36)	2.30 (1.69)	5.34 (2.13)	4.53 (2.12)	5.16 (1.72)	1.50 (0.93)	3.56 (2.25)
Planned use	2.71 (1.68)	2.91 (1.82)	4.10 (1.70)	4.39 (1.97)	4.76 (1.94)	2.27 (1.51)	6.25 (1.24)	5.65 (1.54)	5.04 (2.07)	1.83 (1.15)	4.03 (2.18)
General attitude
Overall benefit	4.00 (1.97)	3.78 (1.70)	4.90 (1.35)	4.82 (1.57)	5.41 (1.32)	3.24 (1.70)	5.97 (1.28)	5.58 (1.15)	5.52 (1.26)	3.39 (1.80)	4.67 (1.77)
Ease-of-use	3.71 (1.87)	3.94 (1.87)	4.74 (1.57)	5.00 (1.58)	5.34 (1.49)	3.94 (1.87)	6.22 (1.01)	5.55 (1.65)	5.56 (1.16)	3.83 (2.01)	4.79 (1.81)
Data sensitivity	4.10 (1.68)	4.63 (1.56)	4.48 (1.41)	4.85 (1.48)	3.81 (1.65)	4.22 (1.62)	4.22 (1.81)	3.81 (1.74)	3.96 (1.95)	4.57 (1.24)	4.26 (1.64)
Social knowledge	2.58 (1.50)	2.78 (1.79)	2.77 (1.48)	5.06 (1.12)	2.75 (1.70)	3.09 (1.72)	3.19 (1.65)	3.90 (1.56)	3.16 (1.70)	3.22 (1.41)	3.26 (1.71)
Certainty	3.67 (2.11)	4.16 (2.19)	5.13 (1.41)	4.82 (1.65)	5.31 (1.71)	3.12 (1.95)	6.25 (0.92)	5.97 (1.30)	5.56 (1.39)	4.22 (2.15)	4.82 (1.95)
Positive feelings	4.68 (1.42)	5.03 (1.36)	5.13 (1.18)	4.67 (1.63)	5.50 (1.19)	4.22 (1.64)	5.84 (1.22)	5.90 (1.14)	5.76 (1.16)	4.83 (1.56)	5.15 (1.45)
Innovativeness	4.84 (1.83)	5.03 (1.36)	5.58 (1.09)	5.36 (1.27)	5.59 (1.10)	4.47 (1.61)	5.50 (1.37)	5.65 (1.38)	5.52 (1.23)	4.91 (1.65)	5.25 (1.43)
Lifestyle benefits
Money	38.2%	26.5%	11.8%	0.0%	26.5%	2.9%	5.9%	50.0%	19.2%	0.0%	18.5%
Safety	0.0%	5.9%	8.8%	0.0%	5.9%	14.7%	47.1%	0.0%	3.8%	46.2%	12.7%
Time	0.0%	26.5%	38.2%	38.2%	29.4%	29.4%	58.8%	38.2%	34.6%	19.2%	31.5%
Fun	20.6%	17.6%	38.2%	70.6%	38.2%	29.4%	44.1%	41.2%	46.2%	30.8%	37.7%
Easy	11.8%	35.3%	41.2%	50.0%	52.9%	41.2%	67.6%	41.2%	53.8%	19.2%	41.7%
Control	17.6%	20.6%	44.1%	44.1%	44.1%	23.5%	52.9%	70.6%	50.0%	38.5%	40.4%
Advanced	55.9%	50.0%	67.6%	55.9%	73.5%	52.9%	67.6%	55.9%	57.7%	42.3%	58.3%
Modern	50.0%	55.9%	70.6%	70.6%	64.7%	52.9%	76.5%	67.6%	69.2%	53.8%	63.3%
Environmental	58.8%	41.2%	14.7%	0.0%	41.2%	8.8%	2.9%	52.9%	30.8%	3.8%	25.9%
Usability
N (usability only)	26	26	26	26	26	26	26	26	26	26	260
Safe-to-use	5.04 (1.72)	5.46 (1.28)	5.33 (1.37)	5.12 (1.36)	5.63 (1.24)	5.38 (1.17)	5.48 (1.33)	5.39 (1.73)	5.56 (1.47)	5.26 (1.18)	5.37 (1.38)
Understanding	3.26 (1.68)	3.67 (1.69)	4.38 (1.38)	5.12 (1.39)	5.21 (1.44)	3.42 (1.67)	6.04 (0.98)	5.26 (1.39)	5.52 (1.23)	3.61 (1.64)	4.57 (1.72)
Reliability	3.70 (1.49)	4.25 (1.26)	4.46 (1.69)	4.48 (1.90)	5.46 (1.25)	3.54 (1.47)	5.24 (1.51)	5.74 (0.92)	5.56 (1.23)	4.13 (1.39)	4.66 (1.60)
Visitor ease-of-use	3.57 (1.67)	3.33 (1.69)	3.83 (1.66)	5.04 (1.31)	5.00 (1.44)	3.42 (1.72)	5.16 (1.86)	4.96 (1.26)	4.88 (1.54)	3.70 (1.79)	4.30 (1.74)
Privacy	5.00 (1.45)	4.79 (1.38)	4.88 (1.30)	4.32 (1.63)	5.46 (1.50)	4.54 (1.35)	4.88 (1.74)	5.52 (1.50)	5.29 (1.37)	4.65 (1.47)	4.93 (1.49)
Technological capability	4.22 (1.09)	4.21 (1.41)	4.75 (1.57)	5.08 (1.58)	5.21 (1.44)	3.50 (1.50)	5.40 (1.08)	4.39 (1.78)	5.56 (1.16)	3.96 (1.49)	4.64 (1.54)
Fit	4.70 (1.11)	4.92 (1.14)	5.21 (1.18)	5.44 (1.23)	5.83 (1.17)	4.17 (1.40)	5.80 (1.12)	5.65 (1.11)	5.88 (1.09)	4.39 (1.41)	5.21 (1.32)

Note. Quantitative results.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

David Wright is an Associate Professor of Technical Communication at Missouri University of Science and Technology. His teaching and research interest include technology diffusion, digital communication, game studies, and usability studies.

Daniel B. Shank is an assistant professor in the Department of Psychological Science at Missouri University of Science and Technology specializing in the area of social psychology. His research interests include psychological perception and social interaction with nonhumans including artificial intelligence, other technologies, consumer products, and groups of people.

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