The Socio-technical Impact of the Internet of Things: An Exploratory
Mixed Methods Research
Albert Boonstra
and Dustin A. Wiktor-Steffens
1,2 b
Faculty of Economics and Business, University of Groningen, Nettelbosje 2, Groningen, The Netherlands
School of Economics, Fudan University, 600 Guoquan Road, Shanghai, China
Keywords: Internet of Things, Socio-technical Systems, Intentionality, Materiality.
Abstract: This study explores how the Internet of Things (IoT) impacts the socio-technical system of organizations. The
paper adopts a mixed methods research with a qualitatively driven approach. Data from 21 interviews with
experts in the field of IoT and an online survey with 123 IoT professionals were analyzed. Leonardi’s Socio-
Technical System Model (2012) was applied as a lens to examine how IoT influences the organizations’ social
subsystem and how that, in turn, affects both the materiality of IoT and users’ intentionality in the technical
subsystem. The results suggest transformed roles, potentially flattened hierarchies, decreased privacy, and
increased transparency to be the main effects. While apparent changes in the social subsystem cause perceived
threats that strongly influence users’ intentionality, they do not certainly affect IoT’s materiality. Noteworthy,
however, is that irreplaceable users reportedly have the leverage to enforce changes to IoT’s materiality.
The physical world, as we know it, merges more and
more with its digital counterpart. The Internet of
Things (IoT) is driving this transformation we
observe, by raising data collection to an
unprecedented level. Emerging data that might
drastically change the work of people in many
The International Data Corporation (IDC)
forecasts the number of Internet-connected devices
will increase from 30 billion in 2020 to 41.6 billion
by 2025 – excluding general-purpose devices, such as
smartphones, tablets, and PCs. In 2025, IoT devices
will generate 79.4 zettabytes of data, providing
unparalleled insight (MacGillivray & Reinsel, 2019).
How IoT affects adopting organizations is still
opaque. With this high-paced development in mind,
one could perceive a sense of urgency, seeing the
present unfamiliarity with IoT’s socio-technical
On the one hand, technological advancements,
potential applications, and estimated economic
growth through IoT are extensively discussed in
journal articles, business reports, and news media. On
the other hand, sufficient knowledge about the impact
on people that work with IoT in organizations seems
hitherto to be missing from the academic debate.
Literature bodies either focus on socio-technical
systems, which incorporate a general perspective on
people and technology in organizations, or they focus
on IoT, addressing the technical design and
economics (Madakam, Ramaswamy, & Tripathi,
2015). Separately, these streams exist abundantly,
but, as to the authors’ knowledge, research combining
both perspectives has yet to be published, thus
offering many opportunities for research questions at
all levels to be explored and tested in today’s business
Gaining a holistic view of the interaction between
technology and people is critical. Chua and Lam
(2005) argue for the fatality to consider the technical
aspects unilaterally. Even though technical
requirements can be met, the appropriation can be
unsuccessful if the technology does not receive
enough ongoing support from its users. Hence, it is
crucial for the effective use of technologies to
incorporate social aspects. This standpoint is shared
by Boos and Grote (2012) as well as Shin (2014),
saying that understanding and considering the
Boonstra, A. and Wiktor-Steffens, D.
The Socio-technical Impact of the Internet of Things: An Exploratory Mixed Methods Research.
DOI: 10.5220/0009327101770188
In Proceedings of the 5th International Conference on Internet of Things, Big Data and Security (IoTBDS 2020), pages 177-188
ISBN: 978-989-758-426-8
2020 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
interplay between technology and people is a pivotal
success factor. In effect, failing to address both
aspects in a balanced fashion leads to higher risks that
technology implementations will not be used to their
full potential or even remain without success.
IoT’s social impact should not be left ignored
(Shin & Jung, 2012). The current and little
interdisciplinary academic discussion leaves us with
the realization that some aspects of the socio-
technical lens are not sufficiently explored and that
the contemporary relevance of the topic allows for
novel research questions. Using Leonardi’s Socio-
Technical System Model (2012) as a lens, this study
aims to explore how IoT in the technical subsystem
impacts the social subsystem and vice versa (see
Figure 1). Through the presented model, the
preliminary research question can be split into the
following three research questions (RQ): RQ I
addresses IoT’s impact on the social subsystem, RQ
II assesses the impact of changes in the social system
on intentionality, and RQ III pays attention to the
impact of changes in the social system on IoT’s
materiality (compare Figure 1).
Several academics agree that IoT is a collection of
devices equipped with numerous types of sensors that
are constantly connected via the Internet. These
interconnected things collect and deliver precise data
from the physical world without direct human
involvement (e.g., Al-Fuqaha, Guizani, Mohammadi,
Aledhari, and Ayyash (2015); Atzori, Iera, and
Morabito (2017); Madakam et al. (2015).
The network of connected devices that
continuously measures the environment with sensors
generates large amounts of data. Enabled by a
semantic layer, the technology transforms data into
relevant information that holds meaning to the user.
The automated collection of data in an unparalleled
quantity constitutes the central affordance of IoT
(Ouaddah, Mousannif, Abou Elkalam, & Ait
Ouahman, 2017; Shi, Li, Zhu, & Ning, 2018).
Affordances are all qualities of a technology that
define its possible uses (Majchrzak & Markus, 2013;
Volkoff & Strong, 2013).
Socio-technical system theory helps to analyze
the organizational interplay between technology and
people, especially how the affordance influences
employees in their work environment. Because of the
reciprocal relationship, socio-technical systems take
both the technological and the social perspective into
consideration. Paul Leonardi’s (2012) model is
especially suitable to observe IoT through the lens of
the socio-technical system theory, as it incorporates
the mutual shaping of technology and people and has
not yet been used to analyze IoT. Moreover, it
distinguishes the interrelatedness of the two
perspectives, namely the social subsystem and the
technical subsystem, in three main impacts; these
serve as the basis to formulate the research questions
(see center arrows in Figure 1).
Figure 1: Socio-Technical System Model (Leonardi, 2012).
Leonardi describes a socio-technical system
consisting of a social subsystem and a technical
subsystem (Figure 1). The social subsystem is
essentially a coherent whole that is formed by
existing interrelationships between individuals within
the organization. Generally, people that interact and
work together build a stand-alone social subsystem
within a group or organization. Defined by the
relationships among the people in the social
subsystem, it is influenced by various aspects like
their abilities, power, assumptions and beliefs,
knowledge, experience with and expectations about
technology, as well as its affordances and constraints
(Orlikowski & Gash, 1994).
The technical subsystem includes both the person
and the artifact. The artifact refers to the technology
as a non-human entity. It has its own materiality,
which is the set-up of physical and digital materials
in particular forms that matter to the user. Those
properties of the artifact do not change, by
themselves, across differences in time and context.
Materiality produces the affordances and constraints
of an artifact that are activated through intentionality
(Leonardi & Barley, 2008).
Whereas artifacts have materiality, persons have
intentionality, which expresses the desired outcome
they have in mind. When users approach artifacts
IoTBDS 2020 - 5th International Conference on Internet of Things, Big Data and Security
with materiality, they form particular goals or human
agency. The coordination of multiple human agencies
constitutes a social agency (Leonardi, 2012).
A central aspect of the interconnectedness is that
the users’ intentionality is subject to influencing
factors in the social subsystem. To a large extent,
users formulate their goals and decide in which ways
they will proceed using the technology based on their
perception of its possibilities and limitations. Their
opinion about the technology is a result of the
sensemaking process in the social subsystem. Thus,
users have considerable influence on the degree to
which technology affects their working environment.
To accomplish their intentions, people choose to
use certain elements of the artifact’s materiality at a
given time. The artifact’s materiality acts by users
activating material agency, meaning they approach
materiality with intentions. Hence, while materiality
refers to properties of the object, material agency
refers to the way the object acts when humans
provoke it. A clear distinction is necessary because
materiality is rather stable over time, but material
agency frequently changes, depending on who is
making sense of the materiality and which intentions
this user has. The social agency is partly shaped in
response to the material agency of all users in the
system and how they perceive each other’s intentions.
The material agency would not exist without users’
intentions to use the technology (Leonardi, 2012;
Wagner, Newell, & Piccoli, 2010).
The social and material agencies are unlike each
other but create a mutual new structure when both
come together. Leonardi (2012) uses the term
imbrication to explain this occurrence; the agencies
become imbricated in the space of practice. In other
words, individuals make use of the technology. As a
matter of fact, imbrication is the actualization of the
technologies’ affordances. The study shows that
specific imbrications cause changes in the social
subsystem, such as in roles, status, and hierarchies.
Transformations in these abstract formulations can
form new future patterns of imbrication. Vice versa,
these transformations can cause changes in the
rtifact’s materiality and person’s intentionality.
Due to the underrepresentation of a holistic approach
in research, this study is constructed using a
qualitatively driven mixed methods design (Saunders,
Lewis, & Thornhill, 2016). First, semi-structured
expert interviews were conducted to identify and
explain emerging phenomena. Based on the identified
core aspects that emerged from the in-depth
interviews, a questionnaire was designed and carried
out to allow increased generalizability and
triangulation. The quantitative results from the survey
helped to create a clearer picture of the qualitative
interviews. The qualitative analysis is dominant due
to the need to create an initial understanding and
provide the basis to generate theory. Results were
compared across both the qualitative and quantitative
data collection. Ultimately, generated insight was
superimposed onto the presented model to derive
conclusions (Eisenhardt, 1989).
3.1 Qualitative Part
For this study, the primary method is qualitative.
Semi-structured expert interviews with limited access
to documents were used to collect data as the topic’s
novelty gave reason to assume a lack of experience
with IoT of most organizations and employees. A
vastly distributed sample led to conducting interviews
via phone with an average duration of 50 minutes.
Each interviewee agreed to audio recordings for
subsequent transcripts. One pretest call with feedback
was performed to identify logical inconsistencies and
unclear formulations. After transcribing all
interviews, the computer program Atlas.ti was used to
create and categorize codes. The coding of transcript
included a balance of deductive and inductive codes
to ensure theoretical and emerging aspects. The data
was analyzed across experts.
The sample consists of 21 experts from business
and academia from the US, China, India, Germany,
the Netherlands, UK, Spain, and Sweden. All selected
participants are responsible for, or knowledgeable of,
the implementation and development of IoT. 90% are
in leading positions or have notable decision-making
power and staff responsibility. The represented
organizations fall into the following roles: (1) IoT
solution provider with additional services for their
platforms and other use cases (43%), (2) management
consulting firms with dedicated IoT practices (38%),
(3) independent IoT research institutions (10%), (4)
research and consulting firms (5%), and (5) internal
IoT research and development (5%).
3.2 Quantitative Part
An online survey is the quantitative and thus
secondary part of the mixed methods approach. It was
designed to test the reliability of the expert interviews
and to provide more generalizable results. The
questionnaire was based on the research questions
and propositions derived from qualitative expert
The Socio-technical Impact of the Internet of Things: An Exploratory Mixed Methods Research
interviews. Respondents (R) were mainly asked to
evaluate eleven statements along the research
questions on a 5-item Likert scale ranging from
“strongly agree” to “strongly disagree.” The results
were used to support the insight generated through the
primary interviews.
The response rate was 17.6% (N = 168). After
scrutinizing for incomplete responses, unsuitable
professions, and multivariate outliers, a sample of N
= 123 remained. On average, respondents had eight
years of experience in the field of IoT (M = 8.03, SD
= 6.73). The majority reported being direct users of
IoT applications (64.2%). Only 3.3% work for the
government. Most participants work at organizations
with over 10,000 employees (33.3%), with 1-4
employees (29.3%), and with 50-499 employees
. Their location is in Europe (37,4%), North
America (27.6%), Asia (24.4%), South America
(4.1%), the Middle East (4.1%), and in Oceania
4.1 Impact on Social Subsystem (RQ I)
The newly gained access to massive amounts of data
supposedly is the main driver for changes in the social
subsystem. The expert interviews confirm the central
affordance of IoT: “All of a sudden, you are able to
read an incredible amount of sensor data, that really
triggers the change” (R4, personal communication,
2018-04-30). In addition, the interviews suggest that
four dominant aspects in the social subsystem are
affected by the abovementioned information flow.
Each aspect will be considered below.
4.1.1 Transformed Role
Transformed roles are evident since aspects related to
changes in employees’ roles are touched upon during
all primary interviews. Besides, the secondary survey
demonstrates a high degree of agreement among the
sample, as Figure 2 shows:
Figure 2: IoT Influences Roles in the Social System.
6.5% with 500-999 employees, 6.5% with 5000-9999
employees, and 5.7% with 1000-4999 employees.
By influencing tasks and their required skills, IoT
influences employees’ roles in many facets. The
experts imply that these shifts in demands associated
with a particular role are likely to be disrupted in the
age of IoT. Therefore, IoT questions the current roles
of employees: “Jobs […]; job profiles […and],
qualifications are changing. Also important is the
question, which work I will still be able to perform
with my current set of qualifications and also which
qualifications are required due to new technologies.
That is a point that surely influences the whole social
system” (R9, personal communication, 2018-05-08).
After categorizing all codes contributing to the
transformation of roles, the following four prevail. (1)
Gravitation towards an intellectual and digital role:
“It will be essential whether they have an IT
background or whether they manage to obtain that
crucial knowledge” (R16, personal communication,
2018-11-21). (2) Increased focus on core tasks: “Yet,
you could provide a way to get rid of some of that
administrative, nonvalue-added activities and let
them do what they are trained to do” (R4, personal
communication, 2018-04-30). (3) Upskilling
workforce: “[IoT] demands employees to educate
themselves further, both the textual and technical
related competencies.” (R3, personal
communication, 2018-05-02). Lastly, (4)
redeployment of workforce into new role: “These
employees who used to work as crane operators will
be promoted to the supervisory level” (R16, personal
communication, 2018-11-21).
4.1.2 Flattened Hierarchy
The primary interviews suggest that IoT
implementations influence the hierarchy as a part of
the social subsystem. More specifically, interviews
imply the potential to flatten hierarchies, e.g.: “When
you deploy technologies like IoT that can have a side
effect that flattens organizational hierarchies” (R12,
personal communication, 2018-05-01). The
secondary survey supports this (see Figure 3) with
12% strongly agreeing and 41% somewhat agreeing.
Factors causing flattened hierarchies were grouped
into three categories: (1) Gained accessibility of
information: E.g. “[…] information come together at
the top of the hierarchy. IoT could make it possible to
distribute that information more, and that could
result in a flatter hierarchy” (R8, personal
communication, 2018-05-04). (2) Altering power
relations: “[…] the gap between hierarchical levels
could become smaller” (R8, personal
Neither agree
nor disagree
IoTBDS 2020 - 5th International Conference on Internet of Things, Big Data and Security
communication, 2018-05-04). And (3) the
restructuring through redundancy: […I]nformation
processing jobs go away. Simply because you have
technology that learns those jobs” (R12, personal
communication, 2018-05-01).
Figure 3: IoT Flattens Hierarchies.
4.1.3 Decreased Privacy
An IoT-enabled working environment almost
inevitably observes employees and collects data
about them, which are potentially accessible to others.
Losing privacy means being uninformed about
ongoing observations and lacking the freedom to
reject these (Sarwar, Yongchareon, & Yu, 2018).
Decreased privacy raises concerns that seem to
impact the social subsystem strongly. Emerging
concerns are also widely recognized in the provided
documents and the secondary survey (Figure 4) with
37% strongly agreeing and 38% somewhat agreeing.
Figure 4: The Extensive Data Collection through IoT
Triggers Privacy Concerns among Employees.
Privacy is potentially a trade-off for improved
organizational efficiency, as organizations
incorporate more monitoring to increase their
measurable profitability. Hence, this may be an
indicator that profit-driven organizations will keep
touching upon these concerns: “Because surveillance
[…] is an outgrowth of efficiency and bureaucratic
evolution. The highly monitored nature of the world
that we are beginning to experience is a natural
outgrowth of a variety of socio-technical trends” (R6,
personal communication, 2018-05-02).
The protection of privacy is a requirement for
employees to develop trust, enabling them to harness
IoT’s benefits: “[…] you start with trust by doing
these proper [privacy] reviews and implementing
proper safeguards and then after that, hopefully, the
employees do see the benefits and the value” (R4,
personal communication, 2018-04-30). Policies, e.g.,
the European General Data Protection Regulation
(GDPR), limit the neglect of privacy in the course of
efficiency gains. Though, there are significant
national differences, having a decisive influence on
risks related to privacy: “It may be totally different in
Germany, Austria, Switzerland, and Europe,
compared to the United States, China, and Africa”
(R1, personal communication, 2018-05-04).
Additionally, the presence and power of labor unions
representing the workforce diverge across different
Lastly, one expert mentions the possible
occurrence of splits in the social subsystem, reporting
that “in the worst case, it will cleave the social system
in two.” The trigger of faultlines may be the
employees’ tolerance towards privacy concerns: “On
one hand [there are] people who don’t ‘care’ and
make maximum use of IoT and take advantage of it.
They also agree to pay the price in form of data. […]
On the other hand, there will be people who try to
evade IoT completely” (R10, personal
communication, 2018-05-08). A Faultline is a gap
that splits a group into at least two subgroups, caused
by certain attributes that each subgroup identifies
with (Meyer & Schermuly, 2012). The secondary
survey results support this phenomenon as the
majority of respondents (68.3%) agree that “IoT
causes contrasting opinions about privacy, which
create faultlines.”
4.1.4 Increased Transparency
Based on the experts, transparency is about the
continuous accessibility of performance
measurement. Integrated sensors enable
organizations to monitor employees’ actions and
decisions constantly. For instance, a “[…] truck
driver who sits in such a connected truck, of course,
is fully monitorable and it is always clear where he
is, when he drives, when does he stand, how much fuel
does he consume, how much do his colleagues
consume, and so on” (R1, personal communication,
IoT-enabled performance measurements do not
seem to resonate positively with employees:
“Actually, I hardly know any worker who is interested
in his work being measured” (R14, personal
communication, 2018-05-07). The primary
interviews and secondary survey support that
increasing transparency seems to create a threat of
losing one’s autonomy (see Figure 5) with 13.0%
strongly agreeing and 41.5% somewhat agreeing.
Neither agree
nor disagree
Neither agree
nor disagree
The Socio-technical Impact of the Internet of Things: An Exploratory Mixed Methods Research
Figure 5: IoT-Enabled Performance Metrics About
Employees Decrease Their Perceived Autonomy.
The interviews reveal that two factors can
influence the perception of increased transparency
positively. Firstly, educating users regarding the
provided advantages that come with more
transparency. A reoccurring example from the
interviews is improved safety, e.g., through IoT-
enabled trucks preventing accidents. Secondly,
informing users about how gathered insight is utilized
might change the perception from negative to
positive: “When it is ambiguous, when they do not
know what they are being monitored for, it is
definitely negative. But, if, if the company is telling
them upfront that they are not trying to pin-point a
particular driver or put a penalty on a particular
person, but, overall trends which all the trucks
combined generate and hence they know this or that
route is better, where they should refuel the vehicles.
All these kinds of definitions come out, and they know
that they will not be individually monitored, then, I
think, it becomes positive” (R17, personal
communication, 2019-02-12).
4.2 Impact on Intentionality (RQ II)
The gathered interview data show that employees’
intentionality conceivably alters due to changes in the
social subsystem: “Yes, there will probably be
behavioral changes. I would be honestly surprised if
it did not […]” (R1, personal communication, 2018-
4.2.1 Expression of Changed Intentionality
The primary interview data suggest that changes
related to intentionality appear to surface in three
forms of negative behavior: (1) Reduced willingness
to use IoT: “[…] I would say, yes, […] he either
avoids using or avoids using parts of the technology
[…]” (R9, personal communication, 2018-05-08). (2)
Application of workarounds: “[T]he user could try to
use a workaround” (R15, personal communication,
2018-04-29). (3) Resistance towards the
implementation of IoT solutions. Especially privacy
concerns were mentioned as a possible cause for
threats that result in resistance: “You feel like big
brother is watching. I think privacy is one of the
elements that would drive the resistance and
especially in industrial Europe because some of the
other regions are far less concerned about privacy”
(R4, personal communication, 2018-04-30).
4.2.2 Causes for Changed Intentionality
The secondary survey results support that the four
previously introduced social aspects in chapter 4.1
might impact intentionality. The survey respondents
ranked the four social aspects in order of their
potential to provoke resistant behavior: first, privacy
(M = 1.62, SD = .944), second, transparency (M =
2.69, SD = 1.094), third, hierarchy (M = 2.81, SD =
.977), and fourth, role (M = 3.09, SD = 1.116).
While the social aspects constitute the major
influence of IoT on the social subsystem, the primary
interviews infer these changes to translate into two
factors that impact employees’ intentionality: (1)
Perceived threats. Employees do not necessarily fear
the technology but what comes along with it. They
“[…] can be quite fearsome […]. That doesn’t
necessarily have to be with regards to the quality of
the hardware and the software […] but it can be seen
as a certain threat to their job, changes in the
hierarchy, and that creates that he might not adopt
new technologies or refuses them” (R8, personal
communication, 2018-05-04). Therefore, it appears
that changes in the social subsystem can cause threats,
potentially altering employees’ intentionality. These
findings are backed by the survey where most
respondents (58.4%) agree that perceived threats
resulting from changes in the social system alter
users’ intention to deploy IoT solutions (Figure 6).
Figure 6: Perceived Threats Resulting from Changes in the
Social System Alter Users’ Intention to Deploy IoT
(2) Perceived Opportunities. It seems to be crucial
whether employees are aware of their individual
benefits. Therefore, employees would, e.g., neglect
the technology when the added value is invisible or
unclear to them. The individual benefits should
clearly outweigh the costs (represented by the
potential threat): “If they see value in what’s on offer,
then they’ll become comfortable with it over time;
Strongly agree Somewhat agree Neither agree
nor disagree
Neither agree
nor disagree
IoTBDS 2020 - 5th International Conference on Internet of Things, Big Data and Security
They need to see the benefits, […] it’s a trade-off,
right? It’s about how you articulate the value” (R12,
personal communication, 2018-05-01).
The interviews suggest that organizations already
try to avert unfavorable intentionality by involving
employees right from the start. Thus, in advance to
the implementation, perceived threats and
employees’ awareness of individual benefits are
addressed early in the process. Organizations
consider both the human perspective as well as
economic efficiency to be crucial for proper IoT
implementations: “Companies realized that they
must make it right in the beginning to avoid
unpredictable behavior of employees and to avoid
wasting money” (R12, personal communication,
4.3 Impact on IoT’s Materiality
The interviews imply materiality to be less
influenceable than intentionality once IoT is
introduced. The experts’ tendency is that
organizations do not consider adjusting the
materiality due to changes in the social subsystem
once the technical integration is completed:
“Changing the technology, I consider difficult,
changing the use of technology, I consider absolutely
feasible.” (R9, personal communication, 2018-05-
08). Substantial adjustments to IoT’s materiality are
unlikely for three reasons:
(1) Exploitation of performance advantages. The
expert states that “if the output is right, the company
will not change the technology, even if the employee
is dissatisfied or there are other negative effects in the
social system.” IoT solutions will remain the same
unless effects in the social subsystem significantly
impair the performance. E.g. “[…] if the output is not
right, if the employee refuses or develops a
workaround that is not legit anymore, then the
company would be forced to adjust” (R15, personal
communication, 2018-04-29).
(2) The necessity to stay competitive is driving the
application of IoT solutions: “From a corporate
perspective, dealing with IoT is relevant to
competition.” The advantages arise, for instance,
from the following: “If I am faster in the future, if I
reduce machine errors if I can predict downtimes of
the machines and thus prevent them. It's important for
the company to do that” (R3, personal
communication, 2018-05-02). Therefore, adjustments
of the materiality, which are limiting the potential
exploitation of the capabilities may be improbable.
Especially, as IoT is a means to become future proof:
“Personally, I don’t think that these social aspects
can change the architecture. […] Because the
company that decided in favor of the IoT solution. I
mean, they are investing in the future” (R16, personal
communication, 2018-11-21). Evaluating IoT as an
essential element on the digital agenda is also
reflected by the survey results: 46% of the
respondents think that IoT’s importance for firm
performance is somewhat above average, and 39.8%
even think it is far above average.
(3) Problem to reverse the integration of
technological elements of IoT. On the one hand, there
is the view that adjustments are out of the question
since organizations have a set of motives for not
adjusting IoT’s materiality and, therefore, the
disadvantages prevail. 14% of the experts argue that
one cannot just make technology disappear: “It
cannot be ruled out that the properties of IoT
solutions will be changed, but basically, of course, it
is usually the case that once a technology is
integrated, it is difficult to restrain it again” (R1,
personal communication, 2018-05-04). On the other
hand, however, experts emphasize the general
magnitude of the social aspects related to IoT. Their
responses to the latter are all similar to the statement:
“For me, that means that I personally would even put
the social aspects at the heart of an IoT development”
(R15, personal communication, 2018-04-29). Only
10% of the experts can envision organizations
adjusting IoT’s materiality: “I guess, in any scenario
[…] you have to be accommodating to two things, to
your bottom-line, but also to your staff and their
feelings. So, you have to take both into account […].
I can see that there are changes made” (R13,
personal communication, 2018-05-10). In line with
this statement, the secondary survey shows that
46.9% disagreed with the statement that the technical
design of IoT solutions remains unchanged despite
changes in the social system, while only 33.6%
agreed. A potential explanation for this discrepancy
might lie in the stages in time in which social aspects
are incorporated. Organizations address social issues
already before and during the implementation process
of IoT, whereas “changing” materiality implies a
post-implementation stage. The experts unanimously
describe that “[…] especially in the field of IoT […it]
is too costly if you first develop something and then
check the feasibility or user acceptance, etc” (R15,
personal communication, 2018-04-29).
Whether or not organizations adjust the
technology’s materiality depends on a moderating
effect of employees’ leverage over the organization.
Analyzing the interview data, several leverage-
creating attributes were accumulated: expertise,
The Socio-technical Impact of the Internet of Things: An Exploratory Mixed Methods Research
flexibility in mobility, hierarchical level, and unique
skill set. Vice versa, the employer has attributes to
exert leverage over the respective employee with
access to qualified workforce and flexibility in
mobility. Survey respondents generally agree that
employees who possess power within the
organization have a noteworthy influence on IoT’s
materiality (69% agree, and 16.9% disagree). Given
that both employees and employers appear to have
leverage, they may have to be weighed against each
other to assess whether potential changes in IoT’s
materiality need to be addressed or can be suppressed.
5.1 Answering the Research Questions
The primary expert interviews and the secondary
survey results help to explore the impacts of IoT
within Leonardi’s Model (2012). The adjusted model
in Figure 7 presents the discussion’s outcomes.
5.1.1 Impact on Social Subsystem (RQ I)
The results suggest the following four ways how IoT
impacts the social subsystem:
(1) Transformed Role. The results suggest that
employees’ roles will change as IoT enables
increasing automation and massive information
enrichment. In line with the literature, the findings
advise that constant education is crucial to
maintaining a valuable role within the organization
(Bresnahan, Brynjolfsson, & Hitt, 2002).
Computerization, primarily driven by data
acquirement via sensors, increases the demand for
highly educated and creatively thinking roles (Frey &
Osborne, 2017). Therefore, employees must be
prepared to adapt their roles faster in an IoT
accelerated environment.
(2) Flattened Hierarchy. This research proposes
that IoT flattens organizational hierarchies when
information is distributed equally and across all
levels. Information is a source of power (Pettigrew,
2016). When information is available at all levels, it
is most-likely to re-allocate decision-making powers
and flatten hierarchical patterns (Dobrajska,
Billinger, & Karim, 2015). Moreover, IoT can be
responsible for technological unemployment
(Brynjolfsson & McAfee, 2014).
(3) Decreased Privacy. Privacy issues have a
substantial impact on employees’ well-being. To a
degree, security matters can justify employees’
location tracking or video surveillance. Generally,
privacy concerns among employees cause decreased
acceptance of IoT solutions. Bélanger and Crossler
(2011) support that privacy concerns reduce the
intention to use information technologies. Their study
implies four dimensions that cause uneasiness of
employees: (1) nontransparent collection of data, (2)
unauthorized secondary use of data, (3) improper
access to data, and (4) errors in data. The results even
reveal that privacy concerns can be considered as a
cause for passive to active forms of resistance
(Chang, Liu, & Lin, 2015). Also, the occurrence of
faultlines provoked by privacy is possible, separating
the social subsystem into subgroups ranging from
being concerned with privacy issues to not being
concerned with them at all. These subgroups may
increasingly work against each other, harming the
organization (Meyer & Schermuly, 2012).
(4) Increased Transparency. Research of Levy
(2018) about truck drivers in IoT-supported vehicles
comes to a similar conclusion that transparent
performance metrics likely negatively affect job
satisfaction. The underlying reasons may be the felt
loss of leeway and decision freedom. Continuous
controllability through sensors takes away
employees’ autonomy. As a consequence, diminished
autonomy leads to lower job satisfaction and can
cause burnout symptoms (Arches, 1991). On the
contrary, it was also reported that increased
transparency generates data that can facilitate fairness
by providing additional proof, e.g., in the case of
truck accidents.
5.1.2 Impact on Intentionality (RQ II)
The abovementioned four social aspects identified in
this research, do not directly impact users’
intentionality. Instead, transformed roles, flattened
hierarchies, decreased privacy, and increased
transparency, constitute changes as these new
circumstances diverge from the incumbent status quo.
These changes cause perceived threats that ultimately
seem to result in alterations in intentionality. This is
in line with Lapointe and Rivard (2005), describing
that it is the object of change that interacts with initial
conditions and not the technology or a specific aspect
in the social system itself that triggers perceived
In the case of technology adaptation, perceived
opportunities lead to the exploitation of a given
technology or even the exploration to innovate. On
the contrary, perceived threats cause an exploration to
revert or even avoidance of the technology (Bala &
Venkatesh, 2016). This interplay is in sync with the
change equation, describing that the benefit of and
IoTBDS 2020 - 5th International Conference on Internet of Things, Big Data and Security
need for change must outweigh the costs of change
(Beckhard, 1975; Dannemiller & Jacobs, 2016). This
notion is also explained by the equity theory in social
sciences, describing the assessment of gain and loss
of changes (Joshi, 1991).
Hence, perceived opportunities compromise the
moderating effect of perceived threats on
intentionality (see Figure 7). The study suggests that
mainly, the four identified social aspects cause threats
that trigger a range of reactions away from neutral
behavior to passive or active resistance (van
Offenbeek, Boonstra, & Seo, 2013). Therefore,
organizations must ensure to incorporate these social
aspects to reinforce successful IoT implementations
(Bersin, Mariani, & Monahan, 2016; Jones, Derasse,
Chitale, & Negri, 2016).
Figure 7: Adjusted Socio-Technical System Model.
5.1.3 Impact on IoT’s Materiality (RQ III)
The conducted research infers that it is indistinct
whether organizations adjust IoT’s materiality in
response to changes in the social subsystem. On one
side, the findings show that the immense investments
of IoT implementations hamper organizations to
leave their planned course of action, even though
people in the social subsystem express their aversion.
Exploring why organizations do not reverse
technological implementations while facing
substantial headwinds, Keil, Truex, and Mixon
(1995) propose two main factors, the level of costs
and the level of project completion. Both aspects
determine the influenceability of materiality. The
higher the costs and further the progress of
implementation, the less likely adjustments appear. In
their consideration, costs were even more significant
than project progress.
In fact, multiple sources confirm that IoT is
considered to be exceptionally cost-intensive
compared to other technologies. Thus, organizations
are compelled to assess each challenge thoroughly
and plan, design, and deploy all aspects with the
highest diligence (Lee & Lee, 2015; Niyato, Lu,
Wang, Kim, & Han, 2016). The necessity to “do it
right the first time” (R12, personal communication,
2018-05-01) reflects the necessity of great efforts in
change management during the implementation. It is
too costly to adjust materiality because of adverse
responses in hindsight. Nevertheless, the survey
results also point at a perceived high likelihood that
organizations do consider adjustments of IoT’s
technical design due to social changes. However,
some employees have distinctive qualities, such as a
unique skill set, which creates an overall exception to
enforcing adjustments of materiality. Their leverage
makes organizations incapable of ignoring their
criticism unless they exert leverage themselves
through, e.g., their access to a large selection of
qualified applicants. The forces of both parties appear
to have a moderating effect on how changes in the
social subsystem influence the materiality in the
technical subsystem (compare Figure 7).
5.2 Theoretical Contributions
The study is the first to bring a degree of clarity to the
way IoT affects the employee in the social subsystem
by applying the theory of Leonardi (2012). The
reported main effects open the hitherto black box of
social implications provoked by IoT (Shin & Jung,
2012). Moreover, it is the first study to explore how
effects in the social subsystem influence users
The findings confirm the idea that it is an object
of resistance instead of specific artifacts or elements
in the socio-technical system that creates perceived
threats. Employees assess the costs and benefits of the
disruption of their initial state for an upcoming
change. A prevailing perception of a threat will
provoke resistant behaviors, spanning from
avoidance, over applying workarounds, to active
resistance (Lapointe & Rivard, 2005).
The study addressed the influence of social effects
on IoT’s materiality, unveiling indistinct results.
There is ambiguous evidence whether organizations
would adjust the technology due to changes in the
social subsystem. Several incentives keep
organizations from adjusting their IoT solutions.
Among them are, for example, the tremendous costs
that come along with an IoT implementation and the
necessity to incorporate IoT use cases to stay
The Socio-technical Impact of the Internet of Things: An Exploratory Mixed Methods Research
competitive (Keil et al., 1995). However, the results
show a moderating effect of both employees’ and
employers’ leverage over each other. Consequently, a
moderator was added to the model (Figure 7) to imply
the evaluation of, for instance, the employees’
leverage due to a unique skill set versus the
employers’ extensive access to skilled people.
5.3 Practical Implications
Derived from IoT expert interviews, the
recommendations’ suitability is neither limited to IoT
nor should they be understood as exhaustive. First,
the results determine the four core aspects that ought
to be monitored with close attention on the journey to
IoT appropriation. Ideally, before, during, and after
the implementation to detect even slight irregularities
over time and avoid perceived threats.
Second, when perceived threats endanger users’
intentionality, the study suggests presenting
perceived opportunities to be an effective
counteraction. Accordingly, benefits for involved
users should be put at the center of the discussion.
5.4 Research Limitations
Due to IoT’s arguable novelty and (so far) limited
distribution, expert interviews were preferred over
interviews with directly affected employees. While
this method allowed comprehensive insight into IoT
in the socio-technical system, the observations are
more abstract. The majority of survey respondents,
however, reported already being direct users of IoT.
The in-depth analysis of mechanisms had to be
neglected due to the variety of specialist knowledge
among the interviewees. Gathering various examples
from different fields was, nevertheless, more valuable
for a universal understanding.
40% of interviewees are German, which can bias
the results because of the geographical commonalities
such as strong privacy regulations and labor unions.
The supplementary survey was distributed via
professional networks. While reducing the chance of
contextual misunderstandings, the approach inherits a
risk of selection bias and false individual portrayal.
Although IoT can be explicitly described, its use
cases often blur with other technologies. Since it is
the infrastructure and enabler for several themes, it is
challenging to match cause and effect to a distinctive
technology. Therefore, the reader ought to be
reminded that IoT operates among other technologies
that influence findings reciprocally.
5.5 Suggestions for Further Research
This study contributes to laying the foundation for
future research exploring detailed mechanisms
through, e.g., a specific IoT application in an
empirical setting. Thus, the presented adapted model
(Figure 7) can be utilized for case studies to verify its
Furthermore, in the light of practical relevance,
future research should investigate strategies to
counteract disturbances in the socio-technical system
related to IoT.
Numerous scholars and reports (e.g., Shi et al., 2018;
Bhatia et al., 2017; Bersin et al., 2016) emphasize the
magnitude of IoT as it is a driving force for the digital
revolution. Looking at the current IoT research, the
predominant focus on technology and business issues
becomes apparent. Consequently, the social
component does not receive the attention it deserves,
considering its importance after implementation.
At question is in what way IoT in the
organization’s technical subsystem impacts the social
subsystem and vice versa. The analysis shows that
access to an unprecedented amount of data affects
some aspects of the social subsystem more than
others. These are transformed roles, flattened
hierarchies, decreased privacy, and increased
transparency. The findings indicate two moderating
effects in the socio-technical system. Firstly,
alterations in the social subsystem lead to perceived
threats that negatively change users’ intention to use
IoT. However, perceived opportunities through IoT
have a moderating effect as they weaken this
relationship. Secondly, alterations in the social
subsystem may have little impact on IoT’s materiality
due to, e.g., the necessity to remain competitive.
Nonetheless, the relationship between social
subsystem and materiality can be affected by the
respective individuals and their unique
characteristics; employees with arguably important
attributes have leverage to reinforce the relationship,
leading to more technical adjustments. Employers’
leverage, however, can weaken the relationship.
This study aims to raise awareness of the social
impact of IoT, in the hope that future research will
shift its focus beyond technological and economic
opportunities to a more human-oriented approach.
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