ArticlePDF Available

Conception of Smartness: A Design Research on User Experience of Smart Artifacts

Human Behavior and Emerging Technologies

October 2024
2024

DOI:10.1155/2024/4425734

License
CC BY 4.0

Authors:

Gizem Çelebi

Istanbul Technical University

Pınar Özemir

Istanbul Technical University

The domestication of smart artifacts has transformed our homes into hybrid environments of physical and digital worlds. It also has been changing our mindsets, behaviors, meaning attributions to, expectations from, frustrations about, and interactions with smart artifacts. By extension, the smartness definition is reconstructed by users who are the subject of smart artifact experiences. The current study is aimed at uncovering the user experience of smart artifacts with a focus on cognitive and emotional aspects to better understand what users expect when an artifact is identified as “smart.” Therefore, an online research study is conducted to gain insight into the user experience of smart artifacts from content-rich reviews on e-commerce websites. Robot vacuum cleaners, smartwatches, and smart speakers were chosen as exemplary smart artifacts of the study. Because they offer different types of interaction with distinct aspects, our findings indicate that smartness is associated with trust in expertise, emotional engagement, exaggerated evaluation, and intriguing existence concepts about Emotional UX. In Cognitive UX, smartness relates to reducing mental workload, gratifying experience, perceived phenotype, reciprocal acquaintance, trust-building experience, tailored situatedness, shaping sociality, physical competency, and dual enhancement concepts. These findings demonstrate the potential of conceptualization in the early stages of smart artifact design processes.

Analysis of the smartness level smart artifacts.

…

An example from the evaluation of the smartness level: robot vacuum cleaners.

…

The evaluation of the smartness level of 15 smart artifacts.

…

Figures - available from: Human Behavior and Emerging Technologies

This content is subject to copyright. Terms and conditions apply.

Access to this full-text is provided by Wiley.

Learn more

Content available from Human Behavior and Emerging Technologies

This content is subject to copyright. Terms and conditions apply.

Research Article

Conception of Smartness: A Design Research on User

Experience of Smart Artifacts

Gizem Çelebi and F. Pınar Özemir

Industrial Design PhD Programme, Istanbul Technical University Graduate School, Istanbul 34367, Türkiye

Correspondence should be addressed to Gizem Çelebi; celebigiz@itu.edu.tr

Received 3 January 2024; Revised 23 August 2024; Accepted 30 August 2024

Academic Editor: Tze Wei Liew

Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work

is properly cited.

The domestication of smart artifacts has transformed our homes into hybrid environments of physical and digital worlds. It also

has been changing our mindsets, behaviors, meaning attributions to, expectations from, frustrations about, and interactions with

smart artifacts. By extension, the smartness deﬁnition is reconstructed by users who are the subject of smart artifact experiences.

The current study is aimed at uncovering the user experience of smart artifacts with a focus on cognitive and emotional aspects to

better understand what users expect when an artifact is identiﬁed as “smart.”Therefore, an online research study is conducted to

gain insight into the user experience of smart artifacts from content-rich reviews on e-commerce websites. Robot vacuum cleaners,

smartwatches, and smart speakers were chosen as exemplary smart artifacts of the study. Because they oﬀer diﬀerent types of

interaction with distinct aspects, our ﬁndings indicate that smartness is associated with trust in expertise, emotional

engagement, exaggerated evaluation, and intriguing existence concepts about Emotional UX. In Cognitive UX, smartness

relates to reducing mental workload, gratifying experience, perceived phenotype, reciprocal acquaintance, trust-building

experience, tailored situatedness, shaping sociality, physical competency, and dual enhancement concepts. These ﬁndings

demonstrate the potential of conceptualization in the early stages of smart artifact design processes.

1. Introduction

Our lives are gradually becoming network-connected

through smart artifacts and systems that vanish into the

background [1], from vacuum cleaners to cars and whole

home or city systems. Smart artifacts inherently present

complex systems of relations between humans, products,

humans and products, and products and environments that

did not exist before, “one made up of many elements that

interact in a nonsimple way”[2]. Smart artifacts are hybrid

products that exist at the intersection of our physical envi-

ronment [3], and cyberspace consists of bits and bytes [4].

Current technological developments with the impact of

communication and information technologies on design

and production processes lead to the redeﬁnition of almost

every relation. These relations involve unpredictable expec-

tations, preferences, or realities about users—things they

do not know that they do not know yet: “unknown

unknowns”[5], things that we cannot predict until we have

experience with that smart artifact for a while. We mediate

the intangible world through tangible smart artifacts, but

when user experience (UX) is discussed, the intangible UX

is most often addressed [6]. Therefore, investigating the

intangible and tangible worlds of this hybrid system will

enable us to more comprehensively reveal the multilayered

relationality with users.

The experience of a smart ecosystem can be categorized

under cognitive, emotional, and ergonomic UX [7–9]. Cog-

nitive UX mostly focuses on users’perceptions regarding

the aesthetics of a system [7–10]. Emotional UX includes

all emotional reactions such as the pleasure of use, posses-

sion of an artifact, intimate connections with artifacts, and

personal value representation over an artifact [7, 8, 10–12].

Lastly, Ergonomic UX deals with usability, aﬀordances, and

eﬀectiveness from a utilitarian perspective [7–9]. The study

focuses on the Cognitive and Emotional UX of smart arti-

facts and how perceived UX aﬀects the perceived smartness

concept. Cognitive UX and Emotional UX can reveal

Wiley

Human Behavior and Emerging Technologies

Volume 2024, Article ID 4425734, 19 pages

https://doi.org/10.1155/2024/4425734

referential aspects of an experience that encompass the

meaning of an experience [13] and users’perceptions about

selected smart artifact groups, which can be associated with

both the perceived UX and the perceived smartness concept.

There were results related to function-oriented situations

(i.e., task achievement) as the subject of Ergonomic UX,

pointing out the usability aspects of the anatomy of any

experience that most users are generally concerned about.

However, the scope of the study focuses on revealing Cogni-

tive UX and Emotional UX-related concepts.

The proposed study diﬀers from human–computer

interaction (HCI) studies in terms of its design-oriented per-

spective and the methodology used. The social and psycho-

logical dimensions of the smartness concept are discussed.

As a result, in this study, smart “products”will be mentioned

as smart artifacts. Because nonhuman agents are not

approached merely as products that are “things that are

grown, produced, or created, usually for sale”or merely as

objects that are “things that can be seen and touched but

are not alive”[14, 15]. These are approached as artifacts that

are taken into account with social, cultural, and psychologi-

cal contexts; “objects that are made by a person, especially

something of historical or cultural interest”[16]. And when

the term artifact is used, both products, services, and systems

that are made by a person are included.

The focus is on perceived UX and perceived smartness

because the complex relationality between these agents has

many levels that are both use-base and meaning-base.

Accordingly, research on perceived UX about perceived

smartness can show how the UX oﬀerings of designed smart

artifacts are perceived and how this perception aﬀects the

overall perception of smartness. The research is aimed at

obtaining conception categories related to UX and the

smartness phenomenon that reveals how users perceive

and give meanings to smart artifacts. These conceptions

can be used in future design studies of smart technology

integration to design balanced, optimal relations between

these agents.

2. Background

2.1. Smartness Concept in Literature. The smartness of an

artifact is deﬁned by many scholars in the context of diﬀer-

ent scales of research. There are juxtapositions and enhance-

ments of deﬁnitions based on the previous studies. Based on

the existing literature, a deﬁnition of a smartness map is

created as a synthesis to capture the overall approach to

the smartness concept by scholars that is presented in

Tables S1, S2, and S3. The literature review is conducted

by using the keyword terms of smart products, smart

artifacts, smart objects, and smart devices.

A smart artifact comprises Internet of Things (IoT) inte-

gration, providing lifecycle support and hardware character-

istics that support smart artifacts’performative and

deﬁnitive characteristics which are the scope of this study

in terms of what a smart artifact is. The technical character-

istics of smart artifacts are out of scope in this study. Because

the individuals as the end-users are the primary subject of

the smart artifact experience that builds and reconstructs

the deﬁnition of the smartness concept in each experience

they have.

In terms of “performative”characteristics, smart artifacts

consist of personalization, connectivity, improved function-

ality, improved interaction, and collecting, processing, and

providing data capabilities. They oﬀer personalization based

on consumer needs, wants, and eﬀects that allow the users to

choose and combine modalities [17–21]. They have network

capability via Wi-Fi connection to at least one network to

other agents on the internet that provides “connectivity in

multiple forms: one-to-one connection, one-to-many,

many-to-many”and P2P connection to “eﬃciently commu-

nicate with other products, services, and users [17, 19,

22–29]. By being “directly or indirectly digitally augmented

and connected”to the processing environment and to the

events of the real world through real-time mapping systems,

they have access rights to objects, ambient resources, and

devices to act jointly and exchange personal information

[17, 18, 27, 30–32]. Their improved capabilities expose mul-

tiple, new, and complex functions, whether provided by the

physical embodiment of communication functionality or

by manufacturers of third-party providers, that provide

use-value, perceptual qualities, better functionality, or ser-

vices that produce useful results through activities that make

them hyperfunctional or multifunctional [18, 30, 31, 33–39].

They extend what users can do with the technology by oﬀer-

ing higher usage behavior, enriching themselves with digital

functionality, and “connecting to external services and

exploiting other objects’capabilities”[27, 40–42].

Smart artifacts are reactive by creating a medium for

“two-way communication between themselves, each other,

and people,”and they continuously interplay and “start

new acquaintances, exchange information, and connect

and collaborate toward a common goal with external ser-

vices”[23, 35, 42–46]. They provide improved optimal

P2U interaction with new usage behaviors, seamless UX,

multimodal natural interfaces, natural product-to-human

interaction, and novel human-technology interaction

methods [17, 18, 40, 41, 47–50]. They oﬀer human-like

interaction that is intuitive to use, create an “optimal rela-

tionship between users and themselves,”“assist in gaining

knowledge about themselves or taking action,”and adapt

to the actors of the interaction that results in increased

relationship-based service and personalized values. They

communicate with the environment eﬀectively to create an

“optimal relationship between users and themselves”[19,

31, 34–36, 38, 45, 49, 51–54]. They collect, provide, and pro-

cess information by sensing, logging, and interpreting infor-

mation generated within themselves and around the

neighboring external world in which they are situated [28,

29, 36, 55–58]. They can process real-time information and

collect and broadcast related context information, their

users, and functionality automatically and transparently by

“computing situational context from sensor data”[31, 44,

45, 50, 52, 59]. They are traceable and can sense, gather, pro-

cess, interpret, transmit, learn, actuate, retain, or restore

information, whether its designers specify it or not. They

can “externalize the knowledge of what it consists of, what

its parts are, and their interrelationship”and “exchange

2 Human Behavior and Emerging Technologies

information about themselves with other digital artifacts or

applications”[30, 36, 39, 49, 60, 61]. The proactivity, adap-

tivity, awareness, autonomy, anticipation, ﬂexibility, and

self-explanatory characteristics are grouped under the deﬁn-

itive category of the deﬁnition of the smartness map. Smart

artifacts can proactively cooperate and “make provisions of

instant user control”by “sensing and using input and output

capabilities of the environment”[17, 19, 22, 27, 29, 35, 40,

44, 47, 50, 58, 62–64]. They are adaptable to diﬀerent situa-

tions and to users by having adaptive algorithms, can recog-

nize “situational and community contexts,”and can use data

to adapt product behavior in time based on user needs,

desires, responses, and tasks [17, 19, 22, 23, 27–29, 36, 47,

62]. They adapt their structure from “minor adaptations to

major changeovers”and have environmental agility “while

preserving their organization [25, 44, 65–68]. They are con-

text-, location-, business-, situation-, real-world, culture-,

self-, and user-aware artifacts [17, 19, 22, 23, 26, 29, 31, 36,

47, 50, 62]. They are aware of their characteristics, product

history, functionalities, user, environment, and situations

and can use the information available to “infer contextual

information related to usage”[31, 38, 40, 52]. They can

“think for themselves”to self-control operations with auton-

omous system decisions and interactions with the users, and

they can “take actions on behalf of users”without human

intervention [17, 25, 26, 28, 32, 33, 35, 40, 44, 50, 58, 59,

68, 69]. They can make smarter choices based on diﬀerent

contexts relevant to their destiny and “act in the world by

adapting their structure”by “applying automated capabilities

and other physical, informational, technical, and intellectual

resources”[29, 39, 49, 65]. They are capable of anticipating

users’plans and intentions for suggestions proactively and

capture the user context, expertise patterns, activities, and

preferences by “automatically identifying, distilling, and

reusing important patterns of product use”[17, 19, 27,

29, 36, 47]. They are ﬂexible to provide instant physical

and social use conditions to provide “ﬁtness for purpose”

[28, 34, 40]. Lastly, smart artifacts are deﬁned as “self-

explanatory”and have semantic self-description [17, 36].

2.2. Change in Form-Function Duality. The use of an artifact

was explained by its form, as in the phrase “form follows

function”in the past. Paper cutting is done with the collab-

oration of scissors and hands; the movement that enables

cutting originates from the hand, and the scissors are like

an extension of the user’s body. However, smart artifacts

are now embedded with invisible IoT technologies in the

form of microchips, sensors, software/digital logic, and dis-

tributed networking capabilities [27, 34]. That leads them

to be black boxes with a weak correlation between form

and function. Newly integrated technological artifacts such

as “smart screens”perform the most collaborative interac-

tions with various screens [70]. This standardization of

interaction modes leads to a lack of full bodily understand-

ing of smart artifacts. As a result, the incompleteness of

newly integrated smart artifacts leads to proposed usage sce-

narios being illustrative dictations. The technology may

impose possible limitations on modes of interaction, may

be too vague for the user to understand and interact prop-

erly, or may present interactions that are strikingly similar

to each other in diﬀerent contexts. In some cases, some

smart artifacts have even begun to perform activities far

removed from traditional modes of use, leading to further

confusion and complexity, such as smart refrigerators that

allow internet surﬁng or becoming a tool for socialization.

These transformations also caused usage to become more

mysterious day by day. We cannot even guess anymore.

The indiﬀerence to interaction modes may indicate that

our design approach may be shallow and needs more

in-depth study. Smart UX, by deﬁnition, creates complex

situations.

2.3. Relationality Between Smart Artifacts and Users. The

interaction modes of smart artifacts can be described as a

language that functions between the artifact and users,

playing a role in shaping and transforming the user as a

subject. Smart artifacts diﬀer from conventional artifacts

due to the dominant intangible interaction modes enabled

by “ubiquitous computing”that vanish into the background

of our everyday lives [1]. Tangible interactions are promi-

nent in the direct use of artifacts. But if a user only inter-

acts with an artifact in tangible ways, we no longer deﬁne

that interaction as smart. IoT technology pervades every

interaction and relation, coexists, transforms, and likens

them to itself. And it also aﬀected the already existing arti-

facts’behaviors. Artifacts have become multi in any sense:

multifunctional, oﬀering multimodal natural interfaces,

and multiple methods of interaction [17, 40, 71]. However,

the relationship between users and artifacts broke oﬀ. Now,

the user’s role is mostly limited to giving commands on a

touch screen and waiting for the task to be done for them

by a smart artifact. We call the individual a user, but the

actual task is done by smart artifacts that are context-aware,

adaptive, proactive, ﬂexible, and autonomous. They can

behave logically based on the processing of collected data,

but there are inherent limitations to this due to their pro-

gramming. They generate solutions to situations, but their

actions are not conscious. These characteristics give smart

artifacts the ability to generate user- and situation-speciﬁc

solutions, but by focusing on perceived smartness, the ques-

tion arises of what makes an artifact be identiﬁed as smart

by the individuals.

Focusing on relationships with users, Streitz et al. [72]

categorized smart artifacts into two types: system-oriented

smart artifacts can make decisions based on previously col-

lected data; in this case, the artifact is proactive without con-

sulting interested users [72]. However, in some cases, this

may be disturbing for users. People-oriented smart artifacts

empower users to make them smarter in their decision-

making and taking-action processes [72]. In this case, smart

artifacts still collect data but inform users to determine the

following actions. By providing information about what is

happening at that moment, in that situation, and in context,

this process results in users making smarter decisions. It can

be said that in the context of focus distribution in smart arti-

facts, the emphasis is still on the system-oriented approach.

There are ways to involve users in the process, but in most

cases, the steps of the activities are handled through

3Human Behavior and Emerging Technologies

machine-to-machine interaction. We are still informed

through other smart artifacts like our smartphones.

Norman claims that standardization in use provides

advancement in usability [70] and introduced the “activity-

centered design”approach to standardize the designed arti-

fact that can be used by “almost anyone in the world”[73].

We can overcome the problem initiated by individualities

by developing an in-depth understanding of the activities

deﬁned as “a coordinated, integrated set of tasks”to be

performed by artifacts and their users [73]. But we redis-

cover the world through our experiences; each observation

depends on the position of the observer and the particular

situation; therefore, there cannot be an absolute standard-

ized observer [74]. We can say that knowledge that is even

slightly related to UX cannot be absolute and should be

considered a research subject. The aﬀordances [3] of smart

technology not only allow us to standardize activities and

interaction modes but also allow users to customize these

interactions. A common language is required to interact

with smart artifacts, but internationally accepted standards

are cumbersome for users tasked with learning those stan-

dards [70]. Complexity is inevitable in the smart artifact

UX, but confusion is a problem caused by poorly designed

interaction modes and form-function association. Therefore,

smart artifacts need to be understood and approached as

people-oriented artifacts.

Automation can be successful with tedious tasks, but

complex tasks require people’s involvement. Complexity is

overcome once people understand the process for once

[70]. So, in any situation, if the smart artifact can explain

itself clearly, the complexity of the activity will no longer

be a problem. Interaction technology has changed and must

adapt to the user. Because technology changes rapidly, peo-

ple and culture change slowly [70]. It is easier to adapt tech-

nology to people because technology was created for people

by people.

2.4. Perceived and Proposed Worlds: Proposed, Expected, and

Real Experiences. Merleau-Ponty states that words have at

least two diﬀerent meanings, and things do not allow them-

selves to be named by a single word [74]. Wittgenstein also

states that to deﬁne the game concept, aﬃnities between dif-

ferent games can be characterized [75]. This can reveal a

“complicated network of similarities overlapping and criss-

crossing”from small to major as if they were “family resem-

blances”[75]. It can also reveal the limits of the smartness

concept, which we approach by focusing on interaction

modes and perceived UX without specifying a ﬁxed mean-

ing. Because the ﬁxation ultimately leads to frustration by

any of the agents involved in both design and use processes,

resulting in proposed, expected, and real experiences. In a

sense, this approach also applies to interaction modes. We

expect users to act on proposed experiences, but systems

inevitably become understood and used as they are designed

[76, 77] by people for people, and they become appropriate

in use [78]. Users are an integrated part of the system [78],

but the initiative is no longer entirely on the user’s side.

Smart artifacts and users are deﬁned as equal partners in

dialogue; so, appropriation of the technology is essential

for mastery [78]. Therefore, if the technology becomes

incomprehensible and the diﬀerences between the proposed,

expected, and real experience increase, it will lead to

frustration.

The proposed usage depends on the designers’decision

during the design process and can be deﬁned as a promise

made by the designer. Expected usage relates to user percep-

tions of the interested artifact. When users ﬁrst encounter

the artifact, they have an understanding of the artifact, its

usage, and its interaction modes. If the qualities of an entity

are perceived as separate indicators of that entity, each of

the qualities reaﬃrms the uniﬁed entity [74]. However, we

cannot understand the overlap between these qualities and

their bounding with each other to become a uniﬁed entity

as a whole [74]. The qualities of entities are related to our

senses, and the only deﬁnition of these qualities can be a

human deﬁnition. Because the embodied object addressed

by the external object with the quality is deﬁned by us

[74]. Therefore, explicit and implicit characteristics will

not be separated, and both will have an impact on our per-

ception, experience, and interaction with smart artifacts.

Additionally, tools deﬁne the activities [73]. As a result,

when a user has experience with smart artifacts, the real

experience may diﬀer from both the proposed and expected

experience. The perceived smartness of an artifact depends

on UX, and this could be just seeing the artifact, having

hands-on experience, or just a virtual interaction through

diﬀerent modes. Understanding the users’perception of

these modes of interaction will lead to the understanding

of smart artifacts.

Perceived UX can be explained concerning the aﬀor-

dances oﬀered by artifacts. All aﬀordances exist regardless

of any agent’s awareness [79]. Users may have no idea about

what smart artifacts have to oﬀer, but smart artifacts still

oﬀer this action. Interacting with a smart artifact may con-

sist of a variety of aﬀordances that go unnoticed by users.

In new adoption cases, users will discover this over time.

Therefore, it can be said that perceived UX requires the user

to be aware of the aﬀordances. It may also be related to the

form-function association, the extent to which the smart

artifact expresses its aﬀordances through its form and modes

of interaction. Relationally, perceived smartness can be

understood over user perceptions through both material,

sensory, and experiential characteristics. It is also about

users’meaning attributions. The ways users construct mean-

ing about smart artifacts also have an impact on perceived

UX and perceived smartness.

2.5. Previous Studies. There are studies in the literature that

investigated the smartness concept but with diﬀerent focus

areas, contexts, or exemplary artifacts. Seymour [80] investi-

gated how the users perceive devices as “smart”by con-

ducting surveys and interviews to explore the relationship

between perceived smartness and ethical concerns about

smart home devices. Rijsdijk and Hultink [51] conducted a

study to measure consumer responses about smart products

and found that the product smartness dimensions aﬀect the

innovation attributes of compatibility, observability, com-

plexity, perceived risk, and relative advantage. Building upon

4 Human Behavior and Emerging Technologies

that, Lee and Shin [81] conducted a study on consumers’

perceptions of the smartness characteristics of smartphones

to understand the impact of product smartness on consumer

satisfaction. Their study is based on Rijsdijk and Hultink’s

[51] ﬁve smartness dimensions of ability to cooperate,

adaptability, autonomy, multifunctionality, and reactivity

and how these dimensions can inﬂuence perceived product

smartness that can lead to customer satisfaction [81]. They

used questionnaire and survey methods to gather data and

applied structural equation modeling [81]. The customers’

attitude toward the use of smart products is the focus of their

study to understand the “perception transfer from perceived

product smartness to product satisfaction”[81]. Makkonen,

Salo, and Pirkkalainen [82] studied perceived intelligence in

physical robots, software robots, and chatbots in a work con-

text to investigate the eﬀects of intelligence dimensions on

overall perceived intelligence. Lee [83] studied to develop a

scale to measure the smartness of a product free of product

category to study the reasons for the smart product prefer-

ences of consumers [83]. Rhiu et al. [84] conducted a study

to analyze the UX of smartphones in terms of product

smartness by using tweets from Twitter as data. Rokonuzza-

man et al. [44] conducted a study to understand the under-

lying characteristics of smart objects that make consumers

perceive them as smart by building on the Rijsdijk and Hul-

tink [71] and Rijsdijk and Hultink’s [51] conceptualizations.

They used scale development and structural equation

modeling combined with questionnaires and asked the par-

ticipants to provide their deﬁnitions, motivations, and attri-

butes that make an artifact smart.

Some studies applied a similar approach as ours to the

perception of diﬀerent concepts. N. Kashive, Powale, and

K. Kashive [85] researched the perceptions of the users

regarding artiﬁcial intelligence’s role in e-learning experi-

ences and their eﬀects on the perceived ease of use, perceived

eﬀectiveness, and perceived usefulness to understand the

overall satisfaction with e-learning. Babic, Orehovacki, and

Etinger [86] conducted a study to investigate the level of per-

ceived experience of students and perceived performance of

intelligent personal assistants in an educational context by

using the measuring attributes for perceived UX as aes-

thetics, usefulness, playfulness, attitude toward use, satisfac-

tion, pleasure, loyalty, and reputation.

2.6. The Relation Between Perceived UX and Perceived

Smartness. The smartness concept in academia is poly-

phonic; there is no consensus on the deﬁnition criteria of

smart artifacts. There are juxtapositions in the deﬁnitions,

or the same characteristic is identiﬁed by a relatively diﬀer-

ent concept by diﬀerent scholars, as shown in the smartness

deﬁnition map in Tables S1, S2, and S3. These categories

constitute the overall perception of the smartness of an

artifact, and the level of performance in each dimension

aﬀects the perception of smartness [82]. However, although

the smartness of an artifact has a strong connection with

the customer experience and corporate performance

improvements [81], there is a lack of smartness deﬁnition

agreed upon in academia from the user’s perspective; they

are mostly overly technological-oriented [83].

UX is the consequence of “a person’s perceptions and

responses from the use and/or anticipated use of a product,

system, or service”[87]. It is a comprehensive ﬁeld that

covers physical and psychological behaviors and reactions

before, during, and after product use [88] and comprises

perceptions in interaction that include “eﬀectiveness, eﬃ-

ciency, emotional satisfaction,”and the quality of the rela-

tionship between the user and the artifact or service [9].

Understanding the UX is fundamental to understanding

the interaction between technology and humans [89]. The

users are the subjects that lead the technology deﬁnition,

functions, and scope [90]. UX, by its nature, is identiﬁed

completely by the users who have no requisite to understand

how an artifact or service works [9]. As the individuals are

the end-users of the smart artifacts, the deﬁnition of smart-

ness can be dependent on the users’perception of these

smart artifacts. Diﬀerent people can attribute diﬀerent

meanings to the smartness concept [91]. The characteristics

of the technology, user, and context-speciﬁc perceptions

aﬀect the perception and adoption of smart services [92].

A shift in perspective to focus on the practice of HCI can

uncover human capabilities, motivations, and values [93].

We approach the matter of subject from a user-oriented per-

spective focused on the experience, especially on the cogni-

tive and emotional side of the experience, because the users

are the ones who know the artifacts [94], and the user’s sub-

jective experience with an artifact and perception of interac-

tion create emotions and meanings [95].

The overall user judgment related to UX concerns their

perception of distinct quality aspects [96]. For example, Rijs-

dijk and Hultink [51] state that a product is identiﬁed as

smart if it is autonomous. Autonomy is a smartness charac-

teristic of a smart artifact. However, individuals are reluctant

to leave the entire decision-making authority to artifacts

[97]. Their preferences about the level of smartness may also

involve some level of human control, although the theoreti-

cal perspective says the opposite [97, 98]. So, when we

approach the concept of smartness, the perception of indi-

viduals can diﬀer from the deﬁnitions made by scholars

and technological-oriented characteristic deﬁnitions.

As researchers, we approach the smartness of artifacts

from an objective point of view. We state that whether an

artifact has integrated IoT technology, anticipation, or

awareness, it can still be identiﬁed as “dumb”by the users.

The smartness of an artifact is not just dependent on the def-

initions made by scholars, developers, or designers. The

individuals as the end-users of these designed and produced

artifacts who have one-to-one interaction daily have a voice;

their individual experiences are taken into consideration

overall and can deﬁne which artifact can be deﬁned as smart

or not. The previous studies show us there is a relation

between the perception of users about the UX that comprises

their opinions about the deﬁnitive and performative aspects

of smart artifacts and the perceived smartness concept. In

previous studies, researchers approached this topic in diﬀer-

ent focus areas.

Secondly, when we talk about user perception, the smart-

ness of a smart artifact can be individual-speciﬁc and depends

on the overall UX of the user, their needs, expectations,

5Human Behavior and Emerging Technologies

frustrations, concerns, emotions, and meaning attributions.

UX is the outcome of the combination of the user’sinternal

state, which is inﬂuenced by the design artifact’s and the con-

text characteristics of the current situation [99]. It is worth

investigating how the smart artifacts are identiﬁed as smart

by the individuals. Hence, we used the smartness deﬁnition

map as a base to evaluate 15 diﬀerent smart artifacts to select

the most suitable exemplary smart artifacts for the case study.

Third, most people construct an understanding of a new

technology by usage [9]. Their mental models about the

smart artifacts formed in the use process include assess-

ments of the beneﬁts, operation styles, and risks they foresee

[9]. Based on the previous studies, we think perceived UX

inﬂuences the perceived smartness concept. Perceived UX

covers all expectations, needs, emotions, and mental models

of the users in the occurring experience, and this can con-

tribute to revealing the understanding of the individuals

about the smartness concept. Our study diﬀers from earlier

mentioned studies by the main focus on the Cognitive and

Emotional UX perspective that aﬀects the perceived smart-

ness concept. Cognitive UX is about the user’s perception

and evaluation of the use of smart artifacts [100], and Emo-

tional UX is about the emotional change or responses stim-

ulated in the use process of smart artifacts. Also, we did not

focus on a speciﬁc smart artifact, such as a smartphone or

smartwatch, individually. We have diversiﬁed our exemplary

smart artifacts of the study to see the diﬀerent interaction

modes to cover more of a comprehensive understanding of

the UX on the smartness concept. Consequently, the com-

ments made on e-commerce websites about the selected

smart artifacts are the users’comments who had experience

with those smart artifacts; their comments are mostly about

their UX, whether it is positive or negative. Because personal

narratives support explaining behaviors and the use of tech-

nology [9]. Observing, gathering data, and analyzing user

behavior can enhance the experiences designed by making

the designers match their designs to the ways the users experi-

ence [9]. Our approach is to derive this vast amount of

individual-speciﬁc UX comments as input to derive a more

extensive understanding of what can be deﬁned as smart from

the users’perspective. The data is unreﬁned, in vast amounts,

and expressed freely by the users without any inﬂuence, which

could be more eﬀective in acquiring more natural UX opin-

ions [84]. These comments can infer individuals’opinions at

an individual level [101] about their UX, as well as their overall

perception of the smart artifacts. We have eliminated the user

comments on these e-commerce websites that are not related

to UX or the smartness concept. This study approaches the

subject from a people-focused perspective; the smart artifacts

solely exist to support individuals in goals and activities to

meet their needs [102]. They achieve this purpose through

their interactions with individuals that can be both tangible

and intangible, constructing the overall UX of the service pro-

vided and the artifact itself.

3. Materials and Methods

The study is aimed at exploring how the multilayered UX of

smart artifacts aﬀects users’understanding of the smartness

concept, with a focus on Emotional and Cognitive UX. The

selection of exemplary smart artifacts is based on a smart-

ness characteristics map to analyze 15 diﬀerent smart arti-

facts (air conditioner, air puriﬁer, coﬀee machine, cooktop,

dishwasher, dryer, lighting, refrigerator, robot cleaner, smart

scale, smart sleep light, smart TV, smartwatch, smart

speaker, and washer) and evaluate them in terms of their

smartness characteristics. Three smart artifacts are chosen

as the focus: Apart from the tangible and intangible interac-

tion modes, robot vacuum cleaners, smartwatches, and

smart speakers are selected. To obtain an overview of user

insights about the UX of smart artifacts, an online research

study was structured to analyze user comments. The com-

ments derived are analyzed via three levels of thematic anal-

ysis to achieve the conceptualization of the interrelation

between perceived UX and perceived smartness concept.

3.1. Selected Exemplary Smart Artifacts. In the selection of

the exemplary smart artifacts, the researchers conducted

research on existing literature in HCI and design studies that

present a smartness deﬁnition. Derived deﬁnitions are ana-

lyzed by a small-scale thematic analysis and are divided into

deﬁnitive categories to structure a smartness characteristics

deﬁnition map. Based on the existing literature, the overall

characteristics of smart artifacts are grouped under 3 catego-

ries: technical, performative, and deﬁnitive which can be seen

in Tables S1, S2, and S3 in the Supporting Information in

detail. These characteristics of the smartness concept are

used to analyze 15 diﬀerent smart artifacts to select the

most suitable exemplary smart artifacts for the case study.

Promotional texts or manuals of 15 smart artifacts are

derived from websites. After that, the researchers started

to underline the keywords or sentences that can be related

to smartness deﬁnition characteristics and subdeﬁnitions.

Then, if the derived keywords and sentences meet the

criteria, they are placed under sub-deﬁnitions in an Excel

sheet, as seen in Figure 1.

The number of subdeﬁnitions that are met by keywords

or sentences is counted as one to arrive at a total number of

smartness levels in a sense. In Figure 2, robot vacuum

cleaner evaluation is presented.

This evaluation is made for all the smartness deﬁnition

characteristics for 15 smart artifacts. With the cumulative

collection of the data shown in all the graphics, the smart-

ness levels according to the ratio of whether each smart arti-

fact meets the smartness characteristics are visualized in

Figure 3, so that all the smart artifacts’levels can be seen

concerning each other. As a result, the selected exemplary

smart artifacts are a robot vacuum cleaner, smartwatch,

and smart speaker.

This study uses divergent exemplary smart artifacts that

provide diﬀerent interaction modes and participation types

to the individuals to see the diﬀerent dimensions of the

smartness concept concerning UX.

3.1.1. Robot Vacuum Cleaners. Robot vacuum cleaners have

a complex ecosystem that includes both tangible and intan-

gible world entities. They have a home network and Blue-

tooth connection to connect to the internet and mobile

6 Human Behavior and Emerging Technologies

applications to oﬀer control or observe data about the prog-

ress, errors, and any information about their lifecycle. They

also oﬀer connections to mobile applications, so smart-

phones with touch and display screens can be identiﬁed as

a tangible extension of them. They have built-in hardware

interface buttons and display screens that allow users to

control or view data about their process. They have charg-

ing docks that they autonomously plugin. The software

interfaces on the display screen of robot vacuum cleaners

can be at the intersection of both worlds; it is tangible, but

it provides intangible data to observe. The robot vacuum

cleaner does sweeping, mopping, and cleaning activities on

its own. Therefore, the bodily existence of users is in ques-

tion. It has ubiquitous computing characteristics by the abil-

ity to analyze the context that it is located in and has

intangible interaction with users through its graphical user

Personalization

(consumer needs

and aects)

Modalities can

be chosen and

combined

Exchange of

personal

information

Act jointly /

complement

each other

Integration

with

processing

environment

Connection at

least to one

network

Access right to

objects,

ambient

resources, and

devices

Eciently

communicate

with other

products, users,

services

Connect the

statutes, events,

“constellation” of

the real world

111111101111

…aynı zamanda

akıllı saatinizinin

bildirim ve alarm

gibi pek çok

fonksiyonunda da

pratik bir şekilde

düzenlemeler

yapabilirsiniz.

/EN/

…you can also

make practical

adjustments to

many functions of

your smartwatch,

such as

notications and

alarms.

Bluetooth

/EN/

Bluetooth

iOS veya

Android

işletim sistemli

akıllı

telefonunuza

yükleyeceğiniz

VFit+ mobil

uygulamasıyla

…

/EN/

With the VFit+

mobile

application that

you can

download to

your iOS or

Android

smartphone…

…biyolojik

değişimlerinizi

takip etmenize

olanak tanıyan

VFit+

uygulaması

/EN/

…VFit+ app

that allows you

to track your

biological

changes

Adım ve mesafe

ölçümü

Uyku takibi

Menstrual döngü

takibi

Kalp atışı ölçümü

/EN/

Step and distance

measurement

Sleep tracking

Menstrual cycle

tracking

Heart rate

measurement

Değiştirilebilir

kordon

/EN/

Changeable strap

…akıllı

cihazlar

arasında

entegrasyon

sağlayarak…

/EN/

…by providing

integration

between smart

devices…

…akıllı

cihazlar

arasında

entegrasyon

sağlayarak…

/EN/

…by providing

integration

between smart

devices…

Uyku takibi

Menstural

döngü takibi

Kalp atışı

ölçümü

/EN/

Sleep tracking

Menstrual cycle

tracking

Heart rate

measurement

…aynı

zamanda

akıllı

saatinizinin

bildirim ve

alarm gibi

pek çok

fonksiyonund

a da pratik bir

şekilde

düzenlemeler

yapabilirsiniz

/EN/

…you can

also make

practical

adjustments

to many

functions of

your smart

watch, such

notications

and alarms.

Vestel Akıllı

Saat Mavi

(Vestel Smart

Watch Blue)

Bluetooth,

adımsayar, aktivite

takibi,

hareketsizlik

uyarısı, kalori

ölçümü, kalp atış

hızı ölçümü

(sensörler)

/EN/

Bluetooth,

pedometer, activity

tracking, inactivity

alert, calorie

measurement, heart

rate measurement

(sensors)

Vestel V-t

için uygulama

marketleri

/EN/

Application

markets for

Vestel V-t

Şarj süresi,

bellek, uzun pil

ömrü

/EN/

Charging time,

memory, long

battery life

Spor modları

Müzik

kontrolü

Kronometre

Nefes

egzersizi

/EN/

Sports modes

Music control

Stopwatch

Breathing

exercise

Connectivity

Hardware

Personalization

Case example

taken IoT integration Lifecycle

support

Figure 1: Analysis of the smartness level smart artifacts.

IoT integration

Lifecycle support

Hardware

Personalization

Connectivity

Improved functionality

Improved interaction

Pro-activity

Collect/process/provide data

Adaptivity

Awareness

Autonomy

Anticipation

Flexible

Robot cleaner

Self-explanatory

Figure 2: An example from the evaluation of the smartness level: robot vacuum cleaners.

7Human Behavior and Emerging Technologies

interface (GUI) through its mobile application and, in some

versions, via its remote controller. Robot vacuum cleaners

redeﬁne the role of users and the subject–object relation in

sweeping activity by taking over the sweeping activity with

their presence. They are eﬀective in creating a medium to

research the eﬀects of the loss of whole-bodily understanding

of smart artifacts and the lack of bodily activities of users on

the perceived UX and the overall perceived smartness concept.

3.1.2. Smartwatches. Smartwatches act like an extension of

our body. They exist as tangible artifacts and have tangible

world entities, but they mostly oﬀer data through intangible

world entities. They have a home network and Bluetooth

connection to connect to the internet and mobile applica-

tions on smartphones to oﬀer control and observe data

about the progress, errors, or any information about their

lifecycle. They also give information about our health, move-

ments, or notiﬁcations about our social circle from various

other mobile applications. They oﬀer connection to mobile

applications, so smartphones with touch and display screens

can be identiﬁed as tangible extensions of smartwatches.

They feature built-in hardware side buttons and touch and

display screens to allow users to control or view data about

their progress. They have charging docks that we plug into

our laptops with a USB-C connection. Software interfaces

on the display screen of smartwatches oﬀer intangible data

to observe. Smartwatches have new meanings and impor-

tance in our postpandemic lives. Users stuck at home needed

to make time for physical activities to protect their health at

home. So, the perception of smartwatches has changed. As a

wearable artifact, smartwatches act as the embodiment of

our bodies. They do not take over our physical activities

but encourage us to do physical activity.

3.1.3. Smart Speakers. Smart speakers feature AI voice con-

trol. They have a home network and Bluetooth connection

to connect to the internet and mobile applications to oﬀer con-

trol and observe data regarding previous interactions, errors,

or their lifecycle. They exist as tangible artifacts and have tan-

gible world entities, but they mostly oﬀer interaction through

the auditory sensory mode. Voice-recognition and voice-

activated software generate outputs based on home network

connections via Bluetooth connections to smartphones. They

also oﬀer connectivity to mobile applications; therefore,

smartphones with touch and display screens can be identiﬁed

as tangible extensions of smart speakers. They have built-in

hardware interface buttons for connecting to smartphones

or changing the volume, have built-in microphones to detect

our commands, and have built-in light rings to indicate when

they are actively listening or responding. They also have

charging cables/docks and need to be constantly plugged in

to function. In these times, when our homes also become

our remote oﬃces, smart speakers serve as personal assistants

that help us in both personal and work lives. In a way, they

act like extensions of our mind and body.

3.2. Online Research Study Methodology. In order to better

understand what users expect when an artifact is identiﬁed

as “smart,”an online research study is conducted. The

online research study is carried out with content-rich

reviews on e-commerce websites with a focus on the UX of

smart artifacts’cognitive and emotional aspects. Robot

Smart TV

Air conditioner

Air purier

Washer

Dryer

Robot cleaner

Refrigerator

Cooktop

Coee machine

Dishwasher

Smart watch

Smart scale

Smart sleep light

Lighting

Smart speaker

Frequency of met smartness sub-denitions

Analysed smart artifacts

Figure 3: The evaluation of the smartness level of 15 smart artifacts.

8 Human Behavior and Emerging Technologies

vacuum cleaners, smartwatches, and smart speakers were cho-

sen as exemplary smart artifacts of the study. Comments are

derived from Türkiye’s Top 4 e-commerce websites: Trendyol

[103–105], Hepsiburada [106–108], N11 [109, 110], and Ama-

zon [111–113], retrospectively, from 29 April 2023 to 1 Janu-

ary 2022. A huge number of codes have emerged about

Ergonomic UX. Users commenting on e-commerce websites

were concerned about the usability, aﬀordances, and eﬀective-

ness of the purchased smart artifacts. However, since the focus

of the current research is on Cognitive and Emotional UX,

Ergonomic UX outcomes are excluded. The number of com-

ments obtained from e-commerce websites for each smart

artifact can be seen in Table 1.

A total of 6509 online comments were analyzed. The

researchers conducted three levels of the thematic analysis

process to generate conceptualizations from comments to

subthemes, subthemes to parent themes, and parent themes

to concepts in a bottom-to-top approach. Gathered online

comments are collected in separate Word documents and

anonymized by assigning a number to each comment. Doc-

uments are divided into 12 categories determined by “Smart

Artifact Type”and “Source Website.”But since there were

no comments about smart speakers on n11.com, the overall

category number in Atlas.ti was 11 in the ﬁnal. Word docu-

ments created during the analysis process are transferred

separately to the Atlas.ti online qualitative research tool.

Atlas.ti is an online qualitative research tool that allows

researchers to organize, code, group, and create massive data

networks easily and systematically. It is a tool that facilitates

the coding process by allowing color-coding and labeling of

selected quotations by the researcher manually. Currently,

Atlas.ti provides AI-generated categorization for the coding

process, but the researcher used this tool in the past manu-

ally. The software is used only for making the coding process

easier with its feature to reuse the manually created codes in

the ongoing process repetitively. The software also provides

an analysis mode that allows the researchers to view every

code created manually by the researchers. The codes also

contain all the related comments that are tagged with these

codes, so if the researchers want to check because of which

comments this code was created, they can view it easily.

These codes can also be grabbed and dropped easily to an

empty canvas, and from one code to another, the researchers

can make the connections manually. At Atlas.ti, researchers

went through all gathered comments to have a sense of

familiarity to detect resemblances in between comments to

further create groupings under codes. The Atlas.ti software

allows the researchers to create color code labels from

scratch and reselect them in the ongoing process again.

Accordingly, after getting familiar with the data, the

researchers started to create color-coded labels in a generic

way for Cognitive UX- and Emotional UX-related sentences

and bites of comments to generate subthemes and parent

themes. The researchers wanted to make sure that these

codes were not too abstract but rather subthemes that iden-

tiﬁed speciﬁc comments. Following the coding process,

researchers used these color-coded subthemes to create net-

work diagrams and data visualizations that represented the

relations of codes between and within subthemes. In this

process, the researchers check the codes and related com-

ments iteratively to create the relations between subthemes

appropriately. In order not to lose control of network dia-

grams created with large amounts of data, network diagrams

are diﬀerentiated by “Smart Artifact Name+Tangible/Intan-

gible Interaction Mode.”In the process of creating network

diagrams, the codes are colored green, red, and blue accord-

ing to whether they are smart or not. The color green is asso-

ciated with being smart, the color blue with neutral, and the

color red with not being smart.

The analysis process required three levels of thematic

analysis. The thematic analysis method is iterative and needs

the researcher’s familiarity with data to assign them to cate-

gories of description and conceptions in a proper way. The

researchers took their time to become familiar with the data

before categorizing them. All three rounds of thematic anal-

ysis processes can be identiﬁed as a bottom-to-top approach

to achieve an overall understanding of Cognitive UX and

Emotional UX in relation to the perceived smartness con-

cept. In the ﬁrst thematic analysis, comments are categorized

under subthemes that indicate situation-speciﬁc categories.

These subthemes are then analyzed, and the themes that

shaped the categorization of topics under Emotional UX

and Cognitive UX are brought together. Finally, a third-

level thematic analysis is conducted on the themes of Emo-

tional UX and Cognitive UX to relate them to the parent

themes that reveal the general overview of the smartness

concept. The third level of thematic analysis led to concepts

related to Emotional UX and Cognitive UX, which point to

concepts that can be considered in the early stages of smart

artifact design processes.

4. Results and Discussion

The analysis process required three levels of thematic analy-

sis. In the ﬁrst thematic analysis, comments are categorized

under subthemes that indicate situation-speciﬁc categories.

These subthemes are then analyzed, and the themes that

shaped the categorization of topics under Emotional UX

and Cognitive UX are brought together. Finally, a third-

level thematic analysis is conducted on the themes of Emo-

tional UX and Cognitive UX to relate them to the parent

themes that reveal the general overview of the smartness

Table 1: Number and comments derived from e-commerce websites for each smart artifact.

Smart artifact Amazon Trendyol Hepsiburada n11 Total

Robot vacuum cleaner 4 2767 1114 28 3913

Smartwatch 57 1953 518 32 2560

Smart speaker 5 8 23 0 36

9Human Behavior and Emerging Technologies

concept. The third level of thematic analysis led to concepts

related to Emotional UX and Cognitive UX, which point to

concepts that can be considered in the early stages of smart

artifact design processes. A more detailed and comprehen-

sive analysis of these parent themes is presented in the next

section. Quotations are coded and presented in the format of

“Initials of smart artifacts+Comment number”(e.g., the 29th

comment on the robot vacuum cleaner is shown as RVC29).

4.1. Findings About Emotional UX. Smartness concepts

related to Emotional UX emerged as emotional engagement,

exaggerated evaluation, intriguing existence, and trust in

expertise. The generated concepts and the parent themes

they emerged from can be seen in Table 2.

The relation between subthemes and parent themes of

Emotional UX can be seen in Tables S4, S5, and S6 in the

Supporting Information in detail.

4.1.1. Emotional Engagement. Smart artifacts that can per-

form physical tasks, unlike other smart home technologies,

ease the user’s workload and make users self-dependent.

The dependency caused the users to form an emotional

engagement with smart artifacts. Some users see them as

indispensable companions of fellow travelers. Users tend to

individualize smart artifacts and interact with them as if they

were humans. As a result of individualization, some users

deﬁne smart artifacts as “my best friend,”“family member,”

or “my daughter-in-law.”Some users said they talk to robot

vacuum cleaners, deﬁning them as “talkative”or “at odds

with them.”RVC602 said, “I command it to sweep the whole

house, but it draws a new map that is diﬀerent from the cur-

rent map. We are at odds; we can’t get along.”Consequently,

it can be said that the UX creates an indispensable depen-

dence on smart artifacts and oﬀers human-like interaction

that structures emotional engagement in users. Even if there

are challenges in the experience, emotional engagement with

the smart artifacts ensures continued use and satisfaction

with the overall UX. Autonomous mobility has led users to

humanize smart artifacts. As a result, emotionally connected

users tend to name smart artifacts. Looking at the examples,

robot vacuum cleaners are named Alfonzo, Dobby, Hatice,

Katya, R2D2, Sebastian, Saﬁye, Yeter, and so on. Two naming

trends emerged: First, users tended to give names similar to

the names of charladies in real life or ﬁctional cinema (e.g.,

Sebastian, Saﬁye, and Yeter). Second, robotic features led users

to give names from science ﬁction movies (e.g., R2D2).

Although comments about satisfaction lead to very

general subthemes (e.g., not meeting expectations or satis-

ﬁed experience), the number of comments is quite large.

Essentially, the UX of any smart artifact is expected to

be satisfactory at all stages, from purchase to maintenance.

Additionally, since the GUI is the main interaction medium,

satisfaction with the GUI and notiﬁcations emerged as

essential expectations from smart artifacts. Satisfaction from

the GUI and notiﬁcations creates an emotional bond in

users that creates loyalty.

4.1.2. Exaggerated Evaluation. Users tend to idealize smart

artifacts and experiences. Some users have idealized robot

vacuum cleaners, describing them as superheroes or prince

charming. RVC683 said, “Prince charming, a lifesaver prod-

uct. One of the most satisfying products I’ve ever pur-

chased.”Here, reducing the workload of users has a great

impact on idealization.

From a broader perspective, the desirability of a smart

artifact is related to consumer trends and price ranges. Pur-

chasing a robot vacuum cleaner has become a trend during

the pandemic period in Türkiye. It was considered a desir-

able artifact to own. Its price range, which again is not

aﬀordable for everyone but at the same time not too expen-

sive, positioned it as a valuable, desirable, and carefully used

artifact. RVC1167 said, “It has become the product that I

love and value most in my home. Why haven’t I taken it

for years; truly a savior.”Depending on the integration of

this “new technology”into daily life, the evaluation of smart

artifacts is exaggerated. Users perceive the experience as

superior to conventional artifacts. On the other hand, the

meanings attributed to being a smart artifact owner in soci-

ety also aﬀect the evaluation positively.

4.1.3. Intriguing Existence. Smart artifacts are perceived as

smart if they provide intriguing, evocatory, entertaining,

and inspiratory experiences. Even the feeling of untrust cre-

ated by the possibility of interruptions in tasks creates a

desire to observe. Therefore, oﬀering evocatory experience

should be considered both positively and negatively. It is also

considered important to provide a fun experience. Robot

vacuum cleaners are described as cheerful because of their

mobility. Users desire to observe them in action. The sense

of entertainment in the smart speaker experience can be

attributed to the unconventional UX. There are smartphones

or smart home technologies that receive and react to voice

commands. But AI-based humanoid responses, such as

making jokes to users or responding in a whisper when the

user speaks quietly, make the smart speaker’s experience

Table 2: Parent themes about Emotional UX ﬁndings.

Generated concepts Parent themes

Emotional engagement

Individualization

Dependence

Humanized interaction

Emotional connection

Satisfaction

Exaggerated evaluation Idealization

Desirability

Intriguing existence

Evocatory

Entertaining

Inspiratory

Trust in expertise

Productivity

Deliberateness

Deﬁciency

Learning capability

Careless

10 Human Behavior and Emerging Technologies

entertaining. Finally, regarding AI-based, humanoid, fast,

and conversational responses, smart speakers motivate users

to communicate with them. Therefore, approaching the UX

design of a smart artifact in a fun, intriguing way that oﬀers

unexpected, entertaining, motivating, and inspiratory inter-

action modes can positively impact the overall smartness

perception.

4.1.4. Trust in Expertise. It is expected that smart artifacts

will fulﬁll the given tasks devotedly and uninterruptedly,

improve themselves over time, and give trust in their exper-

tise to ensure that there is no decrease in performance. The

productivity of robot vacuum cleaners can be observed from

the enhancement of the home. Users tend to describe them

as if they describe people as hardworking, tired, working like

a soldier, or bored in the process. RVC589 said, “It keeps

giving errors during the mapping process. …returns to its

charging dock, even though it has power. I think it’s bored.”

Deliberateness and being careful and attentive in the

process emerge as factors that positively aﬀect the UX. Being

careless in the process also points to the importance of smart

artifacts’deliberateness. Users who were disappointed with

the work described smart artifacts with humanized adjec-

tives such as maverick, works its head, and confused.

RVC995 said, “…It never sweeps corners, most of the time

it works on its head.”In some cases, the disappointment

caused by a smart artifact not doing its job properly leads

users to describe them as having human deﬁciencies such

as blindness, absent-mindedness, or dementia. RVC833 said,

“There isn’t much of a problem except that it forgets the

map all the time, ours turned out to be a little absent-

minded.”

Finally, one of the main points expected and distinguish-

ing smart artifacts from conventional artifacts is their AI-

based learning capabilities. Learning capability is associated

with the expectation that smart artifacts will learn over time

and improve their work based on what they learn. Even

though trust in expertise is mainly related to the usability

of smart artifacts, the results of the UX create emotions that

lead the users to deﬁne smart artifacts as smart or not.

Therefore, the learning capability of smart artifacts and

eﬀective communication to convey information about their

processes are essential to make users feel trustful in the

expertise of smart artifacts.

4.2. Findings About Cognitive UX. Smartness concepts

related to Cognitive UX emerged as dual enhancement,

reducing mental workload, gratifying experience, perceived

phenotype, physical competency, reciprocal acquaintance,

shaping sociality, trust-building experience, and tailored

situatedness. The generated concepts and the parent themes

they emerged from can be seen in Table 3.

The relation between subthemes and parent themes of

Cognitive UX can be seen in Tables S7, S8, and S9 in the

Supporting Information in detail.

4.2.1. Dual Enhancement. As a result of the integration of

smartphones, the place smartphones occupy in users’lives

is obvious. Smart artifacts that reduce the need for smart-

phones by providing notiﬁcations or automated task com-

pletion are deﬁned as liberating those free users from

smartphone addiction.

On the other hand, smart artifacts that do the tasks for

users and oﬀer remote control or access to information are

seen as an extension of the user’s body as if they were pros-

theses. RVC520 said, “It is hand and feet to me; it sweeps all

over the house.”Users feel like they have done the task

Table 3: Parent themes about Cognitive UX ﬁndings.

Generated concepts Parent themes

Dual enhancement

Liberating

Automation

Learning capability

Prosthesis

Reducing mental workload Psychological support

Gratifying experience

Dependence

Smartness

Satisfaction

Productivity

Superiority

Labor-saving

Relieve

Sustainability

Hygiene

Perceived phenotype

Appeal

Brand identity

Desirability

Physical competency

Durability

Technological

Deﬁciency

Aﬀordability

Reciprocal acquaintance

Novice-friendly

Age-friendly

Compelling

Comprehensibility

Demanding workload

Ease of installation

Shaping sociality

Humanization

Entertaining

Animated

Pet-friendly

Child-friendly

Trust-building experience

Privacy

Trust

Security

Tailored situatedness

Customization

Dimensions

Context-dependency

11Human Behavior and Emerging Technologies

themselves, even though the actual task is done by smart

artifacts. When considering smart artifact UX, the concept

of disappearing computers should be taken into account.

Finally, continuous learning capability through updates

allows the UX to be evaluated positively since updates pro-

vide dual enhancement in both the lifecycle of the smart arti-

fact and the user’s experience. The UX should be taken into

consideration to enhance both the users’experience and the

smart artifacts’processes. If it liberates the users from the

physical and mental workload and provides constant feed-

back about the work process, the users are satisﬁed with

the UX and deﬁne smart artifacts as smart.

4.2.2. Reducing Mental Workload. The automated working

capability of smart artifacts enables users to relieve the bur-

den of daily household chores and thus provides psycholog-

ical support to users. RVC970 said, “… The robot takes the

burden of the places to be swept from you, both physically

and mentally.”Instant measurement and feedback of users’

health data in wearable technologies provide psychological

support by making users feel that they are paying attention

to their health. The presence of smart artifacts on users’bod-

ies and constant notiﬁcations motivate users to take good

action regarding their health. SW440 said, “I never take it

oﬀ,it’s always on... Calculating and evaluating my sleep

helps me psychologically.”Considering that society attri-

butes meaning to smartwatch owners as being someone

who cares about their health, the increasing self-conﬁdence

of smartwatch users is a newly emerging trend.

Smart artifacts that reduce users’workload by perform-

ing physical jobs make users feel good and create an emo-

tional connection with users. RVC526 said, “May God not

separate it from us, I have oﬃcially established an emotional

connection with a device.”Therefore, taking over the activi-

ties from users also reduces the mental workload of users.

These taken-over activities can be both physical and mental

work; users feel the presence of a helper, assistant, or mentor

by their side. Reducing mental workload leads to relief from

duties and motivation for future activities and provides psy-

chological support.

4.2.3. Gratifying Experience. The usability of smart artifacts

comes to the fore and aﬀects the UX at the most fundamen-

tal level. Productivity and usability are about Ergonomic UX,

but they also impact Cognitive UX. Dissatisﬁed users

described robot vacuum cleaners as simple carpet sweepers,

while others described them as monsters that oﬀer a

higher-than-expected experience. For example, RVC459

said, “It puts your daily mess out of sight. In short, it’sa

complete carpet sweeper.”Also, the quality of the artifact

and the functions it oﬀers are related to the level of satisfac-

tion with the UX, as SS3 said, “This device is a real beast/

monster when it comes to music.”

In some cases, the expected satisfaction level was

exceeded. For a smart artifact to create satisfaction and be

evaluated positively in terms of UX, it has emerged that it

must provide a UX that creates a sense of superiority over

other similar smart artifacts, other brands, or models. Here,

when there is a way to do a task beyond what the user can

do, the level of satisfaction also increases.

Dependence on smart artifacts has been formed due to

their productivity which is seen as the user’s right hand.

According to users who stated that they could no longer

do without it, smart artifacts that create self-dependence

are considered smart. SW28 said, “Honestly, I didn’tknow

I needed a watch until I had it.”

Satisfaction with UX is associated with labor-saving pro-

cesses that ease the user’s workload, save time, and make life

easier. It results in users feeling relief because users expect

convenience and want comfort and convenience in every

use case of any smart artifact. SS7 said, “It is a quality prod-

uct that will be extremely convenient for anyone who has no

problems with English.”Additionally, being energy-saver

and sustainable positively aﬀects the UX of smart artifacts.

Hygiene also needs to be considered in relevant use cases

of smart artifacts. Overall, the smartness level of a smart arti-

fact has an impact on Cognitive UX. SW473 said, “An 8-

year-old boy didn’t like it, a digital clock with no features;

it’s a shame for the money spent.”Accordingly, it can be said

that a gratifying UX will ensure users deﬁne the UX and

smart artifact as smart.

4.2.4. Perceived Phenotype. Appeal, originality, brand iden-

tity, and desirability of the smart artifacts are associated with

the perceived phenotype that aﬀects the Cognitive UX and

perceived smartness level. The stylish appearance is per-

ceived positively, and brand identity is associated with the

artifact owned. Being visually similar to another brand prod-

uct led to meaning attribution transfer; the brand identity of

the “better”artifact transferred to the more aﬀordable brand

artifact owned. SW498 said, “Everyone who sees it thinks it’s

an Apple Watch.”

Desirability is associated with meeting user expectations.

Some smart artifacts are perceived as a well-deserved

expense due to their price range. In some cases, users deﬁned

exempliﬁed smart artifacts as showpieces that oﬀer mediocre

functional options and are not worth buying. RVC2207 said,

“It just collects dust, that’s all. It’s not worth that much

money. It can only be used for daily carpet sweeping pur-

poses. The reason why it is so praised is nothing but people’s

vanity.”The general perception of smartwatches in society

and the identity of the smartwatch owner have led users to

the desire to own a smartwatch. The fact that it is a desired

product may also be related to the fact that smartwatches are

frequently given as gifts. Therefore, the aesthetics of both

hardware and software components will inﬂuence the overall

perceived smartness and satisfaction with the smart artifact

UX. The phenotype of smart artifacts must be considered

at a broader level, encompassing brand identity, that is, ref-

erences to aesthetic appeal and the smart artifact itself.

4.2.5. Physical Competency. Durability, technology, and

aﬀordability, which are generally related to ergonomics, are

related to the physical competency of smart artifacts, which

aﬀects the Cognitive UX and their level of smartness. The

durability of hardware components and the deﬁciency of

intangible elements such as software positively aﬀect the

12 Human Behavior and Emerging Technologies

perception of smartness. IoT technology, automation, and

remote control are newly adopted technological elements

that users have become familiar with in their lives in recent

years. Accordingly, the smart artifact experience is associ-

ated with a perception of innovation that has not yet become

obsolete. And ﬁnally, aﬀordability is perceived as a positive

feature of the UX. The physical competency of hardware

and software components is related to usability, but it also

aﬀects the perceived UX and smartness. Because these are

the means of interacting with smart artifacts.

4.2.6. Reciprocal Acquaintance. Comprehensibility needs to

be evaluated in two ways. The ﬁrst is related to the user get-

ting used to the usage process that s/he is not used to. If it is

adiﬃcult process for users to get used to, it may even lead to

the abandonment of smart artifacts. Secondly, the language

the smart artifact uses in its notiﬁcations and whether it

understands the given commands correctly. “The watch

types messages by dictation almost ﬂawlessly, although it

makes a lot of typos,”said SW8. Inaccurate or incomprehen-

sible notiﬁcations create a feeling of incomprehension and

negatively aﬀect the UX. RVC590 said, “There is a light noti-

ﬁcation on any button, but there is no sign that it is con-

nected. I still can’tﬁgure it out as the language is foreign;

I’m trying.”Since the smart speaker works via voice com-

mands, it must correctly perceive what the user says, give

appropriate reactions, and provide clarity in feedback. This

also relates to the use of foreign languages. SS21 said, “There

is only one ﬂaw, and that is not the product, but the lack of

Google’s Turkish voice patch.”As in every stage of use, ease

of installation is expected from smart artifacts. The longer or

more complex the process, the more negatively users rate the

overall UX. No part of the UX should be overwhelming for

users. The fact that a smart artifact requires intense eﬀort

from its user creates a negative perception.

Related to all these, the smartness of the artifacts is

related to smart artifacts being novice and age-friendly. It

is important for beginners and the elderly to feel comfortable

from the beginning during the usage process. For novices

and the elderly to adopt smart artifacts into their lives, both

tangible and intangible interactions need to be welcoming. “I

think it would be a good start to get involved in wearable

technology,”said SW15. RVC2440 said, “We are very

pleased. It is a savior for my parents because they are old

people, and we are working.”The complexity of tangible

and intangible interactions is perceived as not smart. As a

result, the UX of smart artifacts can be considered from nov-

ice and age-friendly perspectives. The smart artifact must

learn and become familiar with its context and its user while

also providing the user to be acquainted with itself easily.

4.2.7. Shaping Sociality. Shaping the sociality between users

with smart artifacts is attributed to ‘smart’artifacts. Users

have tended to humanize smart artifacts due to their smooth

and unconventional ways of interacting and their mobility

features. Smart speaker users describe the artifact as a good

assistant with its human-like voice and sentence structures.

SS4 said, “When I try to search for something in Turkish

(song, etc.), we don’t get along very well.”The mobility of

smart artifacts is perceived as entertaining but unpredictable

in some cases. It also enables users to perceive mobile smart

artifacts as pets; animation can be handled in diﬀerent ways

to provide an enjoyable UX. RVC635 said, “My mother

named it Pakize. It wanders around like a cat.”It should also

be taken into account that the unpredictability of an ani-

mated smart artifact should not cause discomfort to users,

pets, and children. “My grandson is scared, so I use it (robot

vacuum cleaner) when he leaves,”said RVC916. As a result,

to provide a child-friendly UX, the UX of every smart arti-

fact must be evaluated from the child’s perspective. Smart

artifacts are agents responsible for shaping sociality with

their users; therefore, this issue should be approached com-

prehensively. Diﬀerent agents share the same environment

with them (elders, novices, children, and even pets), and

their expectations should also be taken into account when

considering the smart artifact UX.

4.2.8. Tailored Situatedness. Tailored situatedness emerged

in customization, context-dependency, and hardware

dimensions. Adjustable tangible and intangible aspects of

smart artifacts have a positive eﬀect on UX and smartness

levels. RVC746 said, “…I can separate the rooms. If you

want, you can have the whole house or by choosing a speciﬁc

room.”Suitability to users and speciﬁc contexts is perceived

as smart. An optimum UX can be provided by taking into

account diﬀerent contexts and situation scenarios, such as

summer use and winter use, for families with or without

children or for speciﬁc user proﬁles. RVC1637 said, “I use

it eﬃciently in the summer; it cannot vacuum the thicker

carpets that I use in winter.”Situatedness can be related to

context, user proﬁles, and environment; therefore, diﬀerent

use scenarios can be discussed to provide tailored situated-

ness in multiple ways.

4.2.9. Trust-Building Experience. Smart artifacts that have

integrated cameras and microphones or require unnecessary

amounts of personal information raise privacy concerns. In

case of any negligence or mistake regarding privacy, users

tend to immediately give up the use of smart artifacts.

RVC1009 states, “None of this information (required during

installation) is required for it to operate or be controlled. If

someone’s goal was to spy on you, that would be ideal with

their camera.”Within the scope of both tangible and intan-

gible interactions, smart products need to convince users

that they are careful about privacy and take reassuring mea-

sures. SW13 said, “The password feature is activated when

you take it oﬀyour wrist. Some protection, no activation

without a password.”

Additionally, smart artifacts with instant shadowing and

security precautions features are seen as smart in emergen-

cies. After the recent earthquake disaster in Türkiye, users

turned to owning smartwatches for safety reasons in case

of emergencies because of GPS location detection. SW24

said, “I bought it for communication purposes after the last

earthquake disaster.”And, SW422 said, “…I can track my

daughter instantly.”Finally, smart artifacts should make

users trust themselves that the task will be completed.

RVC602 said, “…I don’t trust to run it when I’m not at

Human Behavior and Emerging Technologies

home.”Consequently, smart artifacts that provide privacy

precautions, the feeling of protection from spying, or even

emergencies make the users feel trustful. It should be consid-

ered that if there is hesitation about privacy, users will aban-

don the use of the smart artifacts and perceive the UX

negatively.

5. Conclusion

This online research study is conducted as a part of research

for the ongoing PhD study at Istanbul Technical University

Graduate School Department of Industrial Design. To com-

pare the results of our study with similar studies, previous

studies that are conducted with a broader approach or are

not speciﬁcally focused on one exemplary smart artifact such

as smartphones [82] or physical robots [83] are selected.

Rokonuzzaman et al. [44] created a Smartness of a Thing

(SoT) scale based on Rijsdijk and Hultink’s conceptualiza-

tions and used this scale to measure consumer perception

of product smartness. Their study is based on a qualitative

study by critical incident technique (CIT) with a structured

questionnaire which is combined with open-ended ques-

tions. Followingly, they conducted a reliability analysis with

“Cronbach’s alpha and composite reliability”[44]. And their

outcomes are structured as theoretical implications and

managerial implications. Our focus is on enhancing the ini-

tial phases of the design processes of the smart artifacts.

Their scale consists of 10 diﬀerent dimensions: “ability to

cooperate, autonomy, environmental agility, learning, nov-

elty, personality, real-time information processing, two-way

communication, upgradable, and visual appeal”[44]. When

we examine these dimensions, ability to cooperate, auton-

omy, environmental agility, learning, novelty, real-time

information processing, and upgradable dimensions deﬁni-

tions can be categorized as performative/functional dimen-

sions of smartness that are related to usability, eﬃciency,

and ergonomics. Personality, two-way communication, and

visual appeal dimensions can be related to Cognitive UX

and Emotional UX. However, there is no comprehensive

research dedicated to these topics.

Lee [84] studied to develop a scale to measure the smart-

ness of a product free of product category to study the rea-

sons for the smart product preferences of consumers; the

study is based on an in-depth discussion through a literature

review and “scale-development process that consists of item

generation, item reduction, scale validation, reliability, and

validity test”[84]. Their ﬁndings comprise “eight factors of

multifunctionality, human-like touch, ability to cooperate,

autonomy, situatedness, network connectivity, integrity,

and learning capability”[84]. Apart from the human-like

touch factor, the rest of the factors that emerged again can

be categorized as performative/functional factors. Human-

like touch can be related to Emotional UX as it comprises

the deﬁnitions of smart artifacts working like a human,

being thoughtful, having a human-like touch, or personality

like a human [84]. However, our study excludes the Ergo-

nomic UX-related concepts from the start which consist of

performative and functionality-related subthemes and par-

ent themes and diﬀers from their studies [44, 84] by a qual-

itative approach that is solely focused on Cognitive UX and

Emotional UX to understand what is expected by the users

when an artifact is identiﬁed as smart, apart from technolog-

ical enhancements. The reliability of this study is provided

by the anonymity of the large number of user comments

derived from multiple e-commerce websites. These com-

ments were made by a huge number of anonymous users,

and even though they were made in diﬀerent timeframes,

there are aﬃnities between them that lead to clustering

under generalizable concepts. It can also be said that these

outcomes are not a ﬁnal result, but the methodology shows

a way of generating conceptualizations about smart artifacts

as an approach that can be used in the initial phases of the

design process of smart artifacts.

When we focus on the ﬁndings of the current study,

apart from utilitarian ways of performing a task, Emotional

UX and Cognitive UX should be considered in the early

smart artifact design processes. As the ﬁndings about Emo-

tional UX point out, emotional engagement, exaggerated

evaluation, intriguing existence, and trust in expertise con-

cepts could be guidelines to create engaging UXs and user

ﬂows in both tangible and intangible interactions. Data

obtained through UX research focusing on diﬀerent inter-

action modes was used to analyze the overall perceived

smartness concept. Emotional engagement creates depen-

dence on smart artifacts as if they are a part of the user’s

life and provide continued use and satisfaction from the

UX. As a result, user perceptions about the UX of the

related smart artifacts could be exaggerated by users at a

satisfactory level. The UX should be dealt with more

intriguingly, so it would oﬀer a more entertaining, inspira-

tory, and evocatory experience compared to conventional

artifacts in daily life.

On the other hand, users want to trust smart artifacts

that will perform what they promise. So, error-handling

use cases could be handled smartly to show the users that

even if something goes wrong, smart artifacts would act

upon it intentionally. Focusing on the perceived smartness

concept, it can be said that the user’s emotional reactions

to smart artifacts have an impact on how smart they perceive

the experienced smart artifact. Users of smart artifacts that

create positive feelings and emotional engagement tend to

describe these smart artifacts as smart in their overall

smartness assessment. If the experienced smart artifact per-

forms its task eﬃciently or handles errors successfully, it

creates satisfaction in users which leads them to perceive

the smart artifact as smart enough to achieve the predeﬁned

goal or task.

When we think of Cognitive UX, dual enhancement,

reducing mental workload, gratifying experience, perceived

phenotype, physical competency, reciprocal acquaintance,

shaping sociality, tailored situatedness, and trust-building

experience could be considered. Smart artifact UX could

both enhance the daily lives of the users and their ways of

performing at the same time. With this newly integrated

technology, users expect to have less to think about or be

concerned about. Accordingly, the capabilities of smart

technologies should be considered while designing the

smart experience of smart artifacts to reduce the mental

14 Human Behavior and Emerging Technologies

workload of users. The ﬁndings show that the users expect

improvement in their way of living and also improvement

in smart artifacts because of continuous autonomous learn-

ing in the ways of doing tasks. So, this expectation leads to

the requirement of a gratifying experience. This concept

includes satisfaction both in utilitarian and cognitive ways:

ergonomic and functional satisfaction that is based on

saving time, making lives easier, or reducing the user’s

workload. Cognitively, the UX could oﬀer something unex-

pected to the users that leads to a gratifying experience, or

it could make the user feel superior to have that smart arti-

fact and perceive the smart artifact as superior to similar

other smart artifacts. The perceived phenotype that com-

prises appeal, brand identity originality, and desirability

of the smart artifact comes out as an eﬀective concept that

inﬂuences the perceived smartness level of smart artifacts.

Users are inﬂuenced by the visual appeal of smart artifacts;

the meaning attributions of brand identities are transferred

to the actual smart artifacts. The general perception about

the speciﬁc smart artifact and the owner of a smart artifact

in society also aﬀect the perception of the smartness level

of any smart artifact. This perception is also correlated

with brand identity and the aesthetic appeal of certain

brand artifacts. Physical competency of the tangible and

intangible components of any smart artifact inﬂuences

the UX they provide. So, the UX of any smart artifact that

is evaluated whether positively or negatively results in

aﬀecting the perceived smartness level of the related smart

artifact. In terms of the reciprocal acquaintance concept,

the smartness of artifacts is related to smart artifacts being

novice, age-friendly, and continuous learning processes of

the smart artifact. It is expected that the UX will be easily

understood by novice users or the elderly, and the smart

artifacts improve themselves and provide a better experi-

ence in the process of time. Being able to guide users

and having self-learning capabilities are the distinct charac-

teristics of smart artifacts that diﬀerentiate them from con-

ventional artifacts. Smart artifacts that can create an

environment to interact in unconventional ways create a

diﬀerent social medium for users to experience. These

new ways of interacting with artifacts inﬂuence the users

to humanize the smart artifacts, to bond emotionally with

them, and to have fun with a smart artifact even if its main

goal is not entertainment. The tailored situatedness con-

cept is related to the expectation of customization and

the self-learning capability of smart artifacts. The smart-

ness level of an artifact is perceived as higher as the level

of control in customization of the performance increases

or if the smart artifact can adapt to the situations in diﬀer-

ent contexts of use.

Additionally, with its hardware components, such as

built-in cameras and microphones, the smart artifacts can

ensure the privacy of the users would not be violated, mak-

ing the users feel trustful. This trust-building experience

aﬀects the overall perceived smartness positively. Lastly, in

case of emergencies, the users want to be connected to the

digital world constantly. However, this constant connection

should be dependent on users’requests. So, allowing being

connected all the time but not violating this capability is per-

ceived as a smart experience. If we focus on the perceived

smartness concept concerning Cognitive UX, it can be said

that the users deﬁne smart artifacts as smart if they oﬀer

more than successful task completion or usability-related

achievements. The users tend to expect an improvement in

their lives while also expecting enhancement in smart arti-

fact’s capabilities over time. Regarding tangible interactions,

the users expect the smart artifact to be a durable but aes-

thetically appealing artifact that transfers the meaning attri-

butions of a “smart artifact owner”in society to themselves.

Giving trust in expertise, customizing its behavior accord-

ing to users’behavior patterns, and oﬀering simple, under-

standable communication in both tangible and intangible

interactions make the users tend to identify the smart arti-

facts as smart.

Overall, data obtained from trendyol.com, hepsiburada.-

com, n11.com, and ama-zon.com were ﬁltered with a focus

on Cognitive and Emotional UX. The revealed concepts pre-

sented impact the overall UX of smart artifacts. These con-

cepts show that smart artifacts oﬀer more specialized

functions and UX than conventional artifacts. Perceived

smartness can be addressed through these concepts provided

by the smart artifacts’UX. Rethinking about Emotional UX,

the smartness of a smart artifact is associated with trust in

expertise, emotional engagement, exaggerated evaluation,

and intriguing existence concepts. Regarding Cognitive

UX, the smartness of a smart artifact is associated with a

gratifying experience, reducing mental workload, perceived

phenotype, reciprocal acquaintance, trust-building experi-

ence, tailored situatedness, shaping sociality, physical com-

petency, and dual enhancement concepts. These emerging

concepts can be considered early in smart artifact design

processes.

Although it was an opportunity to observe trends in

user comments with a wide range of diﬀerent comments,

most of these comments were very similar to each other

or pointed to the same subthemes. The comments were very

divergent, and many diﬀerent codes are emerging regarding

Emotional UX and Cognitive UX. However, most of these

codes can be identiﬁed abstractly to identify speciﬁc issues

or to give us substantial insight into the user’s perspective

(e.g., meet expectations, fairly well, and useless). Second,

most of the emerging subthemes were related to Ergonomic

UX. Users commenting on e-commerce websites were gen-

erally concerned about usability, aﬀordances, and eﬀective-

ness of purchased smart artifacts (e.g., about robot

vacuum cleaners “failure in connection to the internet,”

“broken down too quickly,”or “diﬃcult care process”).

But Ergonomic UX is out of the scope of the current study,

so Ergonomic UX codes are excluded from the analysis.

To preserve the integrity and readability of the article,

only the prominent comments used to establish sub-

themes, parent themes, and concepts are given as quotes.

The entire data set consisting of comments is not pre-

sented within the scope of the article. In future work,

our goal is to design case study research to gather insights

from users who have experienced all three exemplary

smart artifacts over a longer period. We aimed to analyze

how diﬀerent interaction modes aﬀect Emotional UX and

15Human Behavior and Emerging Technologies

Cognitive UX outcomes and their eﬀect on the overall per-

ceived smartness concept. Our conceptualization focused

on Cognitive and Emotional UX that is related to the per-

ceived smartness concept can beneﬁt designers to use it as

a tool while designing smart artifacts or apply the method-

ology to their initial research process in the early phases of

the design process.

Data Availability Statement

The dataset is collected from the comments made on tren-

dyol.com, hepsiburada.com, n11.com, and amazon.com.tr

between 29 April 2023 and 1 January 2022. The search bars

of the websites are used for smart artifacts bytyping “akıllısaat

(smartwatch in Turkish),”“akıllıhoparlör (smart speaker in

Turkish),”and “robot süpürge (robot vacuum cleaner in

Turkish)”keywords. The researchers then ﬁltered the search

results by the “top-rated”option and selected the smart arti-

fact with the most comments. Open-source links to the

comments are listed in the references (see [104–113]). Data

used to support the ﬁndings of this study are available from

the corresponding author upon request if needed.

Conflicts of Interest

The authors declare no conﬂicts of interest.

Funding

This research received no speciﬁc grant from any funding

agency in the public, commercial, or not-for-proﬁt sectors.

Supporting Information

Additional supporting information can be found online in the

Supporting Information section. (Supporting Information)

Table S1 shows the smartness characteristics deﬁnition map

structured by the researchers, technical characteristics. Table

S2 shows the smartness characteristics deﬁnition map struc-

tured by the researchers, performative characteristics. Table

S3 shows the smartness characteristics deﬁnition map struc-

tured by the researchers, deﬁnitive characteristics. Table S4

shows the parent themes that emerge under the umbrella of

Emotional UX related to robot vacuum cleaners and the sub-

themes that lead to these parent themes. Table S5 shows the

parent themes that emerge under the umbrella of Emotional

UX related to smartwatches and the subthemes that lead to

these parent themes. Table S6 shows the parent themes that

emerge under the umbrella of Emotional UX related to smart

speakers and the subthemes that lead to these parent themes.

Table S7 shows the parent themes that emerge under the

umbrella of Cognitive UX related to robot vacuum cleaners

and the subthemes that lead to these parent themes. Table

S8 shows the parent themes that emerge under the umbrella

of Cognitive UX related to smartwatches and the subthemes

that lead to these parent themes. Table S9 shows the parent

themes that emerge under the umbrella of Cognitive UX

related to smart speakers and the subthemes that lead to these

parent themes.

References

[1] R. Want, B. N. Schilit, N. I. Adams et al., “The Parctab Ubiq-

uitous Computing Experiment,”in Mobile Computing,T.

Imielinski and H. F. Korth, Eds., vol. 353 of The Kluwer

International Series in Engineering and Computer Science,

Springer, Boston, MA, 1996.

[2] H. A. Simon, “The architecture of complexity,”Proceedings of

the American Philosophical Society, vol. 106, no. 6, pp. 467–

482, 1962.

[3] J. J. Gibson, “The concept of aﬀordances,”Perceiving, Acting,

and Knowing, vol. 1, p. 1, 1977.

[4] H. Ishii and B. Ullmer, “Tangible bits: towards seamless inter-

faces between people, bits and atoms,”in In Proceedings of the

ACM SIGCHI Conference on Human Factors in Computing

Systems, pp. 234–241, ACM, 1997.

[5] C. Cagnin, A. Havas, and O. Saritas, “Future-oriented tech-

nology analysis: its potential to address disruptive transfor-

mations,”Technological Forecasting and Social Change,

vol. 80, no. 3, pp. 379–385, 2013.

[6] G. Chalhoub, M. J. Kraemer, N. Nthala, and I. Flechais, ““It

did not give me an option to decline”: A Longitudinal Analy-

sis of the User Experience of Security and Privacy in Smart

Home Products,”in Proceedings of the 2021 CHI Conference

on Human Factors in Computing Systems, Yokohama, Japan,

2021.

[7] L. Alben, “Quality of experience,”Interactions, vol. 3, no. 3,

pp. 11–15, 1996.

[8] D. Norman and J. Nielsen, “The deﬁnition of user experience

(UX),”2017, https://www.nngroup.com/articles/deﬁnition-

user-experience/.

[9] M. Kuniavsky, Smart things: ubiquitous computing user expe-

rience design, Elsevier, 2010.

[10] M. Hassenzahl, “The interplay of beauty, goodness, and

usability in interactive products,”Human–Computer Interac-

tion, vol. 19, no. 4, pp. 319–349, 2004.

[11] D. Norman, J. Miller, and A. Henderson, “What you see,

some of what's in the future, and how we go about doing it:

HI at Apple computer,”in In Conference Companion on

Human Factors in Computing Systems, p. 155, ACM, 1995.

[12] R. W. Belk, “Possessions and the extended self,”Journal of

Consumer Research, vol. 15, no. 2, pp. 139–168, 1988.

[13] F. Marton and W. Y. Pong, “On the unit of description in

phenomenography,”Higher Education Research & Develop-

ment, vol. 24, no. 4, pp. 335–348, 2005.

[14] “Product deﬁnition,”https://www.oxfordlearnersdictionaries

.com/deﬁnition/english/product?q=pro%2520duct.

[15] “Object deﬁnition,”https://www.oxfordlearnersdictionaries

.com/deﬁnition/english/object_1?q=ob%2520ject.

[16] “Artifact deﬁnition,”https://www.oxfordlearnersdictionaries

.com/deﬁnition/english/artifact?q=art%2520efact.

[17] M. Mühlhäuser, “Smart products: an introduction,”in In

Constructing Ambient Intelligence: AmI 2007 Workshops

Darm-Stadt, Germany, November 7-10, 2007 Revised Papers,

pp. 158–164, Springer, Berlin Heidelberg, 2008.

[18] M. Kynsilehto, T. Olsson, and M. Niemelä, “Issues on user

acceptance and experience in smart interoperability environ-

ments,”in Proceedings of the 14th International Academic

MindTrek Conference: envisioning future media environ-

ments, pp. 178–182, Tampere, Finland, 2010, October.

16 Human Behavior and Emerging Technologies

[19] W. Maass and S. Janzen, “Dynamic product interfaces: a key

element for ambient shopping environments,”BLED 2007

Proceedings, vol. 26, 2007.

[20] I. Kuksa and T. Fisher, “Introduction: design and personalisa-

tion–by a person or for a person?,”in Design for Personalisa-

tion, pp. 1–13, Routledge, 2017.

[21] M. M. Tseng, R. J. Jiao, and C. Wang, “Design for mass

personalization,”CIRP Annals, vol. 59, no. 1, pp. 175–

178, 2010.

[22] W. Maass and U. Varshney, “Preface to the focus theme sec-

tion:‘smart products,”Electronic Markets, vol. 18, no. 3,

pp. 211–215, 2008.

[23] I. Vitali and V. Arquilla, “Conversational smart products: a

research opportunity, ﬁrst investigation and deﬁnition,”in

DeSForM19 Proceedings, 2019.

[24] G. Privat, C. Kintzig, and G. Poulain, Communicating with

Smart Objects: Developing Technology for Usable Persuasive

Computing Systems, Kogan Page Science, 2003.

[25] T. Tomiyama, E. Lutters, R. Stark, and M. Abramovici,

“Development capabilities for smart products,”CIRP Annals,

vol. 68, no. 2, pp. 727–750, 2019.

[26] M. Silverio-Fernández, S. Renukappa, and S. Suresh, “What is

a smart device?-a conceptualisation within the paradigm of

the Internet of Things,”Visualization in Engineering, vol. 6,

no. 1, pp. 1–10, 2018.

[27] P. Mayer, D. Volland, F. Thiesse, and E. Fleisch, “User accep-

tance of' smart products': an empirical investigation,”2011,

http://aisel.aisnet.org/wi2011/9.

[28] S. A. Rijsdijk and E. J. Hultink, ““Honey, have you seen our

hamster?”consumer evaluations of autonomous domestic

products,”Journal of Product Innovation Management,

vol. 20, no. 3, pp. 204–216, 2003.

[29] A. G. Mysen, Smart products an introduction for design stu-

dents, Norwegian University of Science and Technology,

2013.

[30] N. Costa, N. Rodrigues, M. A. Seco, and A. Pereira, “SL: a ref-

erence smartness level scale for smart artifacts,”Information,

vol. 13, no. 8, p. 371, 2022.

[31] H. W. Gellersen, A. Schmidt, and M. Beigl, “Adding some

smartness to devices and everyday things,”in Proceedings

Third IEEE Workshop on Mobile Computing Systems and

Applications, pp. 3–10, IEEE, Los Alamitos, CA, USA, 2000.

[32] F. Hermann, R. Blach, D. Janssen, T. Klein, A. Schuller, and

D. Spath, “Challenges for user centered smart environments.

In Human-Computer Interaction,”in Ambient, Ubiquitous

and Intelligent Interaction: 13th International Conference,

HCI International 2009, San Diego, CA, USA, July 19-24,

2009, Proceedings, Part III 13, pp. 407–415, Springer, Berlin

Heidelberg, 2009.

[33] R. D. Buurman, “User-centred design of smart products,”

Ergonomics, vol. 40, no. 10, pp. 1159–1169, 1997.

[34] S. Kettley, “Interrogating hyperfunctionality,”in In Smart

Design: First International Conference Proceedings, pp. 65–

73, Springer, London, 2012.

[35] S. A. Rijsdijk, E. J. Hultink, and A. Diamantopoulos, “Product

intelligence: its conceptualization, measurement and impact

on consumer satisfaction,”Journal of the Academy of Market-

ing Science, vol. 35, no. 3, pp. 340–356, 2007.

[36] E. Aitenbichler, F. Lyardet, G. Austaller, J. Kangasharju, and

M. Mühlhäuser, “Engineering intuitive and self-explanatory

smart products,”in Proceedings of the 2007 ACM Symposium

on Applied Computing, pp. 1632–1637, Seoul, Korea, 2007,

March.

[37] F. J. Lin, Y. Chen, S. Y. Lu, and Y. Hsu, “The smart grid tech-

nology development strategy of Taiwan,”Smart Grid and

Renewable Energy, vol. 7, no. 5, pp. 155–163, 2016.

[38] D. Skyrme, Knowledge networking: Creating the collaborative

enterprise, Routledge, 2007.

[39] S. Alter, “Making sense of smartness in the context of smart

devices and smart systems,”Information Systems Frontiers,

vol. 22, no. 2, pp. 381–393, 2020.

[40] Y. Dahl, “Redeﬁning smartness: the smart home as an inter-

actional problem,”in 4th International Conference on Intelli-

gent Environments (IE 08), Seattle, WA, USA, 2008.

[41] H. J. Park and H. S. Lee, “Product smartness and use-

diﬀusion of smart products: the mediating roles of consump-

tion values,”Asian Social Science, vol. 10, no. 3, p. 54, 2014.

[42] L. Atzori, A. Iera, and G. Morabito, “From" smart objects" to"

social objects": the next evolutionary step of the Internet of

Things,”IEEE Communications Magazine, vol. 52, no. 1,

pp. 97–105, 2014.

[43] D. L. Hoﬀman and T. Novak, “Emergent experience and the

connected consumer in the smart home assemblage and the

Internet of Things,”2015, Available at SSRN 2648786.

[44] M. Rokonuzzaman, K. K. Kim, K. K. Dugar, and J. Fox,

“What makes an object smart? Conceptualization, develop-

ment, and validation of a scale to measure the smartness of

a thing (SoT),”Journal of Business Research, vol. 141,

pp. 337–354, 2022.

[45] A. Lazar, C. Koehler, T. J. Tanenbaum, and D. H. Nguyen,

“Why we use and abandon smart devices,”in Proceedings of

the 2015 ACM International Joint Conference on Pervasive

and Ubiquitous Computing, pp. 635–646, Osaka, Japan, 2015.

[46] L. Sterling and T. Juan, “The software engineering of agent-

based intelligent adaptive systems,”in Proceedings of the

27th International Conference on Software Engineering,

pp. 704-705, St. Louis, MO, USA, 2005.

[47] M. Kynsilehto and T. Olsson, “Intelligent ambient technol-

ogy: friend or foe?,”in Proceedings of the 15th International

Academic MindTrek Conference: Envisioning Future Media

Environments, pp. 99–106, Tampere, Finland, 2011.

[48] M. Abramovici, J. C. Göbel, and P. Savarino, “Reconﬁgura-

tion of smart products during their use phase based on virtual

product twins,”CIRP Annals, vol. 66, no. 1, pp. 165–168,

2017.

[49] C. Y. Wong, D. McFarlane, A. A. Zaharudin, and V. Agarwal,

“The intelligent product driven supply chain,”in IEEE Inter-

national Conference on Systems, Man and Cybernetics, Yas-

mine Hammamet, Tunisia, 2002.

[50] The Smart Product Consortium, (2007), M. S. From,

J. Kantorovitch et al., “Position paper on realizing smart

products: challenges for semantic web technologies,”Net-

works, vol. 522, pp. 135–147, 2009.

[51] S. A. Rijsdijk and E. J. Hultink, “How today's consumers per-

ceive tomorrow's smart products,”Journal of Product Innova-

tion Management, vol. 26, no. 1, pp. 24–42, 2009.

[52] M. Bilal Ahmed, S. Imran Shaﬁq, C. Sanin, and E. Szczerbicki,

“Towards experience-based smart product design for indus-

try 4.0,”Cybernetics and Systems, vol. 50, no. 2, pp. 165–

175, 2019.

[53] C. Hopp, D. Antons, J. Kaminski, and T. Oliver Salge,

“Disruptive innovation: conceptual foundations, empirical

17Human Behavior and Emerging Technologies

evidence, and research opportunities in the digital age,”

Journal of Product Innovation Management, vol. 35,

no. 3, pp. 446–457, 2018.

[54] W. Reinartz, N. Wiegand, and M. Imschloss, “The impact of

digital transformation on the retailing value chain,”Interna-

tional Journal of Research in Marketing, vol. 36, no. 3,

pp. 350–366, 2019.

[55] D. J. Langley, J. van Doorn, I. C. Ng, S. Stieglitz, A. Lazovik,

and A. Boonstra, “The internet of everything: smart things

and their impact on business models,”Journal of Business

Research, vol. 122, pp. 853–863, 2021.

[56] K. Porter, R. Simons, and J. Harris, “Comparison of three

techniques for scour depth measurement: photogrammetry,

echosounder proﬁling and a calibrated pile,”Coastal Engi-

neering Proceedings, vol. 34, pp. 64–64, 2015.

[57] V. Ramaswamy and K. Ozcan, “Oﬀerings as digitalized inter-

active platforms: a conceptual framework and implications,”

Journal of Marketing, vol. 82, no. 4, pp. 19–31, 2018.

[58] G. Fortino, A. Guerrieri, and W. Russo, “Agent-oriented

smart objects development,”in Proceedings of the 2012 IEEE

16th International Conference on Computer Supported Coop-

erative Work in Design (CSCWD), pp. 907–912, IEEE,

Wuhan, China, 2012.

[59] V. Kumar, D. Ramachandran, and B. Kumar, “Inﬂuence of

new-age technologies on marketing: a research agenda,”Jour-

nal of Business Research, vol. 125, pp. 864–877, 2021.

[60] N. M. do Nascimento and C. J. P. de Lucena, “Fiot: an agent-

based framework for self-adaptive and self-organizing appli-

cations based on the Internet of Things,”Information Sci-

ences, vol. 378, pp. 161–176, 2017.

[61] M. Beigl, H. W. Gellersen, and A. Schmidt, “Mediacups:

experience with design and use of computer-augmented

everyday artefacts,”Computer Networks, vol. 35, no. 4,

pp. 401–409, 2001.

[62] C. Gutiérrez, J. Garbajosa, J. Diaz, and A. Yagüe, “Providing a

consensus deﬁnition for the term" smart product",”in 2013

20th IEEE International Conference and Workshops on Engi-

neering of Computer Based Systems (ECBS), pp. 203–211,

IEEE, Scottsdale, AZ, USA, 2013.

[63] B. Henkens, K. Verleye, and B. Larivière, “The smarter, the

better?! Customer well-being, engagement, and perceptions

in smart service systems,”International Journal of Research

in Marketing, vol. 38, no. 2, pp. 425–447, 2021.

[64] I. C. Ng and S. Y. Wakenshaw, “The Internet-of-Things:

review and research directions,”International Journal of

Research in Marketing, vol. 34, no. 1, pp. 3–21, 2017.

[65] J. Salamanca, “Modeling socially apt smart artifacts,”on

Interacting with Smart Objects, p. 22, 2013.

[66] F. J. Rammig, S. Grösbrink, K. Stahl, and Y. Zhao, “Designing

self-adaptive embedded real-time software–towards system

engineering of self-adaptation,”in 2014 Brazilian Symposium

on Computing Systems Engineering, pp. 37–42, IEEE,

Manaus, Brazil, 2014.

[67] M. G. Mehrabi, A. G. Ulsoy, Y. Koren, and P. Heytler,

“Trends and perspectives in ﬂexible and reconﬁgurable

manufacturing systems,”Journal of Intelligent Manufactur-

ing, vol. 13, no. 2, pp. 135–146, 2002.

[68] P. C. Verhoef, A. T. Stephen, P. K. Kannan et al., “Consumer

connectivity in a complex, technology-enabled, and mobile-

oriented world with smart products,”Journal of Interactive

Marketing, vol. 40, no. 1, pp. 1–8, 2017.

[69] Z. Mani and I. Chouk, “Drivers of consumers’resistance to

smart products,”Journal of Marketing Management, vol. 33,

no. 1-2, pp. 76–97, 2017.

[70] D. Norman, The design of everyday things: Revised and

expanded edition, Basic books, 2013.

[71] S. A. Rijsdijk and H. J. Hultink, “The impact of product

smartness on consumer satisfaction through product advan-

tage, complexity, and compatibility,”in Tomorrow's Product

Today-From Imagination to Implementation, PDMA Research

Conference Proceedings 2002, pp. 177–196, Product Develop-

ment and Management Association, 2002.

[72] N. A. Streitz, C. Rocker, T. Prante, D. Van Alphen, R. Stenzel,

and C. Magerkurth, “Designing smart artifacts for smart

environments,”Computer, vol. 38, no. 3, pp. 41–49, 2005.

[73] D. A. Norman, “Human-centered design considered harm-

ful,”Interactions, vol. 12, no. 4, pp. 14–19, 2005.

[74] M. Merleau-Ponty, The world of perception, Routledge, 2004.

[75] L. Wittgenstein, Philosophical investigations, John Wiley &

Sons, 2009.

[76] S. Bødker, “Computer applications as mediators of design

and use,”DAIMI Report Series, vol. 28, no. 542, 1999.

[77] A. Crabtree, T. Hemmings, and T. Rodden, “Pattern-based

support for interactive design in domestic settings,”in

Proceedings of the 4th Conference on Designing Interactive

Systems: Processes, Practices, Methods, and Techniques,

pp. 265–276, London, England, 2002.

[78] M. G. Petersen, O. S. Iversen, P. G. Krogh, and

M. Ludvigsen, “Aesthetic interaction: a pragmatist's aes-

thetics of interactive systems,”in Proceedings of the 5th Con-

ference on Designing Interactive Systems: Processes, Practices,

Methods, and Techniques, pp. 269–276, Cambridge, MA,

USA, 2004.

[79] B. D. Nye and B. G. Silverman, “Aﬀordance,”in Encyclopedia

of the sciences of learning, Springer, Boston, MA, 2012.

[80] W. Seymour, Re-thinking smartness: designing more ethical

connected devices for the home, Doctoral dissertation, Univer-

sity of Oxford, 2020.

[81] W. J. Lee and S. Shin, “Eﬀects of product smartness on satis-

faction: focused on the perceived characteristics of smart-

phones,”Journal of Theoretical and Applied Electronic

Commerce Research, vol. 13, no. 2, pp. 1–14, 2018.

[82] M. Makkonen, M. Salo, and H. Pirkkalainen, “What makes a

(ro) bot smart?: examining the antecedents of perceived intel-

ligence in the context of using physical robots, software

robots, and chatbots at work,”in In Mediterranean Confer-

ence on Information Systems, Association for Information

Systems, 2022.

[83] W. J. Lee, “Evaluating perceived smartness of product from

consumer’s point of view: the concept and measurement,”

The Journal of Asian Finance, Economics and Business,

vol. 6, no. 1, pp. 149–158, 2019.

[84] I. Rhiu, S. H. Ahn, D. Park, W. Kim, and M. H. Yun, “An

analysis of user experience of smartphone based on product

smartness utilizing social media data,”in In Proceedings of

the Human Factors and Ergonomics Society Annual Meeting,

vol. 60, no. 1pp. 1198-1199, SAGE Publications, Sage CA: Los

Angeles, CA, 2016.

[85] N. Kashive, L. Powale, and K. Kashive, “Understanding user

perception toward artiﬁcial intelligence (AI) enabled e-learn-

ing,”The International Journal of Information and Learning

Technology, vol. 38, no. 1, pp. 1–19, 2020.

18 Human Behavior and Emerging Technologies

[86] S. Babic, T. Orehovacki, and D. Etinger, “Perceived user expe-

rience and performance of intelligent personal assistants

employed in higher education settings,”in 2018 41st Interna-

tional Convention on Information and Communication Tech-

nology, Electronics and Microelectronics (MIPRO), pp. 830–

834, IEEE, Opatija, Croatia, 2018.

[87] ISO 9241-210, Ergonomics of human-system interaction—-

part 210: human-centered design for interactive systems

(formerly: 13407), International Standarts Organization,

Switzerland, 2010.

[88] S. C. Jeong, J. S. Byun, and Y. J. Jeong, “The eﬀect of user

experience and perceived similarity of smartphone on accep-

tance intention for smartwatch,”ICIC Express Letters, vol. 10,

no. 7, pp. 1613–1619, 2016.

[89] K. Hornbæk and M. Hertzum, “Technology acceptance and

user experience,”ACM Transactions on Computer-Human

Interaction (TOCHI), vol. 24, no. 5, pp. 1–30, 2017.

[90] D. MacKenzie and J. Wajcman, The social shaping of technol-

ogy, Open university press, 1999.

[91] A. Cassandra and P. McFadin, Internet of Things: Where does

the data go?, Wired, 2015.

[92] N. V. Wünderlich, F. V. Wangenheim, and M. J. Bitner,

“High tech and high touch,”Journal of Service Research,

vol. 16, no. 1, pp. 3–20, 2013.

[93] K. Kuutti and L. J. Bannon, “The turn to practice in HCI:

towards a research agenda,”in Proceedings of the SIGCHI

Conference on Human Factors in Computing Systems,

pp. 3543–3552, Toronto, Ontario, Canada, 2014.

[94] M. Hassenzahl, “User experience and experience design,”The

Encyclopedia of Human-Computer Interaction, vol. 2, pp. 1–

14, 2013.

[95] M. Hassenzahl, Experience design: Technology for all the right

reasons, Morgan & Claypool Publishers, 2010.

[96] H. Santoso, M. Schrepp, A. Hinderks, and J. Thomaschewski,

Cultural diﬀerences in the perception of user experience,

Gesellschaft für Informatik e.V., 2017.

[97] F. Li, Y. Lu, and D. Hands, “Designing for an AI-enabled

smart service adoption from a user experience perspective,”

in 22st DMI: Academic Design Management Conference:

Impact The Future By Design, pp. 1000–1012, Design Man-

agement Institute, 2020.

[98] H. Yang, W. Lee, and H. Lee, “IoT smart home adoption: the

importance of proper level automation,”Journal of Sensors,

vol. 2018, no. 1, Article ID 6464036, pp. 1–11, 2018.

[99] M. Hassenzahl and N. Tractinsky, “User experience-a

research agenda,”Behavior & Information Technology,vol.25,

no. 2, pp. 91–97, 2006.

[100] X. Dong, Y. Chang, Y. Wang, and J. Yan, “Understanding

usage of Internet of Things (IOT) systems in China,”Infor-

mation Technology & People, vol. 30, no. 1, pp. 117–138,

2017.

[101] E. Schonfeld, Mining the thought stream, TechCrunch Web-

log Article, 2009.

[102] D. J. Cook and S. K. Das, “How smart are our environments?

An updated look at the state of the art,”Pervasive and Mobile

Computing, vol. 3, no. 2, pp. 53–73, 2007.

[103] “Trendyol, Google Nest Mini 2nd Generation Smart Speaker-

Home Assistant,”https://www.trendyol.com/google/nest-

mini-2-nesil-akilli-ev-asistani-hoparlor-siyah-p-

43308127?boutiqueId=61%26merchantId=222627.

[104] “Trendyol, Xiaomi Mi Smart Robot Vacuum Cleaner,”

https://www.trendyol.com/xiaomi/mi-robot-vacuum-mop-

pro-cleaner-robot-supurge-ve-paspas-beyaz-p-

36502435?boutiqueId=61%26merchantId=167992.

[105] “Trendyol,XiaomiMiRedmiWatch2Lite,”https://www

.trendyol.com/xiaomi/mi-redmi-watch-2-lite-siyah-2022-

yeni-model-turkiye-garantili-p-224790061.

[106] “Hepsiburada, Google Nest Mini 2nd Generation Smart

Speaker - Home Assistant,”https://www.hepsiburada.com/

google-nest-mini-2-nesil-akilli-ev-asistani-hoparlor-p-

HBV00000THNGG.

[107] “Hepsiburada, Xiaomi Mi Smart Robot Vacuum Cleaner,”

https://www.hepsiburada.com/xiaomi-mi-robot-vacuum-

mop-pro-beyaz-akilli-robot-supurge-pm-HB00000SDB4A.

[108] “Hepsiburada, Xiaomi Mi Watch Lite Smartwatch,”https://

www.hepsiburada.com/xiaomi-mi-watch-lite-akilli-saat-

black-p-HBV000017CBCS.

[109] “N11, Xiaomi Mi Smart Robot Vacuum Cleaner,”http://www

.n11.com/urun/xiaomi-mi-robot-vacuum-mop-pro-beyaz-

akilli-robot-supurge-1007043?magaza=shoppingbymufabel.

[110] “N11, Xiaomi Mi Watch Lite Smartwatch,”http://www.n11

.com/urun/ipg-xiaomi-mi-watch-lite-smartwatch-ekran-

koruyucu-2-adet-19335299?magaza=serportipg.

[111] “Amazon, Apple Watch SE (2nd Generation) Smartwatch,”

https://www.amazon.com.tr/Apple-Gece-Yar%C4%B1s%

C4%B1-Al%C3%BCminyum-Kasa-%20Spor-Kordon-%

20Alg%C4%B1lama/dp/B0BDHY61B6/ref=sr_1_42?__mk_

tr_TR=%C3%85M%C3%85%C5%BD%C3%95%C3%91%

26crid=YMCFQYU16SGH%26keywords=ak%C4%B1ll%

C4%B1%2Bsaat%26qid=1682014755%26spreﬁx=ak%C4%

B1ll%C4%B1%2Bsaat%2Caps%2C149%26sr=8-42%26th=1.

[112] “Amazon, Bose Home Speaker 500 –Smart Speaker,”https://

www.amazon.com.tr/Bose-795345-2100-Home-Speaker-%

20Siyah/dp/B07G8H8K9J/ref=sr_1_10?crid=

1WY5EW569YS12%26keywords=+ak%C4%B1ll%C4%B1%

2Bhoparl%C3%B6r%2Balexa%26qid=1682507638%

26reﬁnements=p_n_availabil+ity%3A13136583031%

26rnid=13136582031%26spreﬁx=ak%C4%B1ll%C4%B1%

2Bhopar%2Caps+%2C149%26sr=8-10%26th=1.

[113] “Amazon, Xiaomi Mi Smart Robot Vacuum Cleaner,”

https://www.amazon.com.tr/Xiaomi-SDJQR02RR-17061-

Vacuum-%2520Cleaner/dp/B07718TKPR/ref=sr_1_38?__

mk_tr_TR=%C5M%C5%8E%D5%D1%26crid=3P6%

2520C5YASB3Z29%26keywords=robot%252Bs%FCp%

FCrge%26qid=1681985235%26spreﬁx=r%2520obot%

252Bs%FCp%FCrg%252Caps%252C221%26sr=8-38%

26th=1.

19Human Behavior and Emerging Technologies

ResearchGate has not been able to resolve any citations for this publication.

What Makes a (Ro)bot Smart? Examining the Antecedents of Perceived Intelligence in the Context of Using Physical Robots, Software Robots, and Chatbots at Work

Conference Paper

Full-text available

Oct 2022

In recent years, the acceptance and use of intelligent robots and other kinds of intelligent systems have begun to gain more and more attention also in information systems research. Here, many studies have found the perceived intelligence of robots to act as one critical antecedent for their acceptance and use, but few studies have focused on the antecedents of perceived intelligence itself. In this study, we aimed to address this gap in prior research by examining the effects of individual intelligence dimensions on the overall intelligence perception of robots in the work context. In addition, we also examined the potential differences in these effects as well as in the individual intelligence dimensions and overall intelligence perception themselves between three common types of robots: physical robots, software robots, and chatbots. These examinations were based on online survey data from 1,080 present or prior users of robots at work. In summary, we found that adaptability, personality, autonomy, and multifunctionality act as the most influential antecedents of perceived intelligence in the case of all three types of robots. In addition, we also found that software robots and chatbots perform better than physical robots in most individual intelligence dimensions and in overall intelligence perception.

SL: A Reference Smartness Level Scale for Smart Artifacts

Article

Full-text available

Aug 2022

During the last two decades, many products, research projects and prototypes were announced with different characteristics and capabilities, all adopting the “smart” qualifier word. If a smartness property could not be defined simply as true or false, defining a suitable range was not an easy task. This issue led to the proposal of some classification models, frameworks and taxonomies for project classifications, but none of them provide a clear and pragmatic smartness scale able to classify smart artifacts and serve as a reference. This paper aims to propose a smartness scale to help research and non-research communities to better quantify and easily understand the features and autonomy of smart artifacts. The proposed smartness scale considers the main function of physical-device components in smart systems. The provided smartness scale is based on a uni-dimensional typology that defines 12 different smartness levels, created based on our definition of “smart artifact” and by following an evolutionary set of capabilities ranging from traceable-only and sensing-capable artifacts to autonomous, adaptable and self-driven artifacts. In order to show the feasibility of the proposed smartness scale, an analytic model was defined and applied to several research- and market-based artifacts tagged as smart in order to extract their smartness levels.

Designing for an AI-enabled smart service adoption from a user experience perspective

Conference Paper

Full-text available

Aug 2020

Industry 4.0', 'Digitalization', 'Internet of Things (IoT)' and 'Smart Services' have become today's buzzwords due to the advanced development of information and communication technologies (ICTs). Consequently, the world economy has changed from a physical product dominated economy to a more software and service-controlled economy. It is no longer about the product that matters, but it is about the data that is generated by using the product or service. The data arising from the use of products can be used to define new business models and services to foster long-term sustainable competitive advantage. How to create smart services by collecting and using these data is not only an opportunity, but also a challenge for companies to remain competitive in highly dynamic market contexts. Smart services can be defined as services tailored to specific user needs with the help of data and intelligent processing. It requires a deep understanding of users and their particular contexts of use and an intelligent processing of these emergent data. User adoption of smart services should be properly understood, on the one hand; on the other hand, this understanding could be processed to enable smart interventions that support the users and how they interact with this technology on a regular basis. The understanding of user adoption within smart service research still requires considerable attention. A platform to collect, integrate and process user information and their usage data continuously is, therefore, essential to the development of smart services. In this study, an AI-enabled framework called 'Smart Service Blueprint Scape' (SSBS) is proposed to increase the knowledge associated with the user experiences of smart services. The framework demonstrates the elements of smart services by providing an integrated approach from the perspectives of both user experiences and AI system. With the purpose of improving the smart service adoption, three smart mobility service cases were critically analyzed, through making use of the framework to demonstrate how the users' experiences were enabled by the SSBS framework. YouTube movie clips of these three smart mobility services were analyzed to collect the data for illustrating how the SSBS was utilized. Through the qualitative analysis, the values of an SSBS framework were identified through three aspects. Firstly, the interactive relationship with users and service provision of the smart services process is demonstrated. Secondly, the integration of user experience and AI system is further elaborated. Finally, the dimensions reflecting characteristics of smart services are identified: the connection among smart devices, AI and support process. Designers can maintain and communicate with different stakeholders within the smart service delivery process. The framework creates the systematic overview for smart service with the help of AI system.

“It did not give me an option to decline”: A Longitudinal Analysis of the User Experience of Security and Privacy in Smart Home Products

Conference Paper

Full-text available

May 2021

Smart home products aren’t living up to their promise. They claim to transform the way we live, providing convenience, energy efficiency, and safety. However, the reality is significantly less profound and often frustrating. This is particularly apparent in security and privacy experiences: powerlessness, confusion, and annoyance have all been reported. In order to reduce frustration and help fulfill the promise of smart homes, we need to explore the experience of security and privacy in situ. We analyze an ethnographic study observing six UK households over six months to present a longitudinal view of security and privacy user experiences in smart products. We find inconsistencies in managing security and privacy, e.g., contrasting the ease of granting and difficulty of withholding consent. We identify security and privacy issues in repurposing smart home devices – using devices outside of their initial intended purposes. We conclude with recommendations for design in smart home devices.

Understanding user perception toward artificial intelligence (AI) enabled e-learning

Article

Full-text available

Dec 2020

Purpose The purpose of this study is to explore the perception of the users concerning the role of artificial intelligence (AI) in enhancing personal learning profile (PLP), personal learning network (PLN) and personal learning environment (PLE) and their effect on the perceived ease of use, perceived effectiveness and perceived usefulness for enhancing the overall attitude and satisfaction of the e-learning. Design/methodology/approach The data were collected from students and professionals who have ever used the e-learning module, and smart partial least square-structural equational modeling (PLS-SEM) is used to see relations between the different variables. Findings It was seen that the PLE is affecting both perceived ease of use and perceived usefulness. The research has shown that perceived ease of use showed a mediating effect between PLE and attitude and satisfaction. Further satisfaction mediates between perceived ease of use and intention. PLP has come out to significantly impacting perceived effectiveness. The multigroup analysis also showed that the attitude and satisfaction level affecting intention to use the e-learning module differ across the two groups of learners, i.e. gender and type of learners. Research limitations/implications The data are collected from students and professionals who have ever used the e-learning module and wholly based on their perceptions, leading to self-perception bias. Originality/value The current research is trying to integrate the user perception of PLP, PLN, PLE into the framework of the technology acceptance model and see how they impact the overall attitude and satisfaction of the learners. AI can be used to improve them and make e-learning more adherent to the users. AI can play an essential role in generating the right environment by matching the profile of the learner.

Experience Design, Technology for All the Right Reasons

Article

Jan 2010

Marc Hassenzahl

What makes an object smart? Conceptualization, development, and validation of a scale to measure the Smartness of a Thing (SoT)

Article

Mar 2022
J BUS RES

Although there is a growing interest in understanding smart objects, there is no consensus on the conceptualization of smart objects/things in the extant literature. In this paper, we focus on the smart objects/things that make up the larger system known as the Internet of Things (IoT) and measure the smartness of an object from the consumer perspective. We propose the Smartness of a Thing (SoT) as a multidimensional construct consisting of ten dimensions. Across a series of studies, we confirm the validity and reliability of our proposed SoT scale. Multiple validity tests suggest that our SoT scale can be applied to a wide range of research settings and contexts. For managerial application, we suggest a way of creating an index of a SoT score for a specific object. We also provide theoretical and managerial implications of this research.

Knowledge Networking: Creating the Collaborative Enterprise

Book

Jul 2007

David Skyrme

The Smarter, the Better?! Customer well-being, engagement, and perceptions in smart service systems

Article

Jun 2021
INT J RES MARK

Smart service systems – that is, configurations of smart products and service providers that deliver smart services – are striving to increase the smartness of their offering, but potential consequences for customer well-being are largely overlooked. Therefore, this research investigates the impact of smartness on customer well-being (here, self-efficacy and technology anxiety) through (1) customer engagement with different smart service system actors (here, smart products and service providers) and (2) customer perceptions (here, personalization and intrusiveness perceptions) and their associated importance (here, need for personalization and intrusiveness sensitivity). A scenario-based experiment (n = 730) – which is preceded by a systematic review to conceptualize smartness – shows that customers perceive more personalization than intrusiveness in case of higher levels of smartness, resulting in customer engagement with the smart product and to some extent with the service provider. Via customer engagement with the smart product, higher levels of smartness stimulate self-efficacy, especially for customers with a high need for personalization. When customers' need for personalization is high and their intrusiveness sensitivity is low, higher levels of smartness also reduce technology anxiety via customer engagement with the smart product. Hence, the conclusion is: “The smarter, the better!”, whereby the relationship between smartness and well-being (here, self-efficacy and technological anxiety) is significantly influenced by customer heterogeneity. These findings help business practitioners in boosting customer well-being by increasing customer engagement through higher levels of smartness of their service system.

Influence of new-age technologies on marketing: A research agenda

Article

Jan 2020
J BUS RES

This study focuses on four key new-age technologies – the Internet of Things, Artificial Intelligence, Machine Learning, and Blockchain – and their respective roles in marketing. Specifically, the study examines each of these four technologies in depth, to understand their key elements, the domains in which they operate, and current use cases pertaining to these technologies. The adoption of these new-age technologies is expected to have an impact on the outcomes for firms and customers. However, these are dynamically evolving technologies that have not yet been completely explored and whose full potential has yet to be uncovered. This study presents some research questions that are pertinent to key entities (firms, customers, intermediaries, developers, and regulators), and which merit deeper investigation in the future. This study also highlights major areas that need managerial focus in the adoption of these new-age technologies.

Conception of Smartness: A Design Research on User Experience of Smart Artifacts

Abstract and Figures

Recommended publications

Investigating User Experience Disparity in E-Commerce: A Case Study of Computer Science Professional...

What makes an object smart? Conceptualization, development, and validation of a scale to measure the...

Spielerische Erhaltung und Förderung der mentalen Gesundheit. Wie beeinflusst Gamification das Nutzu...

User Experience at Work: Four Perspectives on What It May Mean