IoT Adoption Barriers: Evidence
from Data Collection
The survey was
developed using the Qualtrics web tool. Qualtrics is a web-based platform for
developing surveys, collecting and storing data and conducting other data
collection activities. Two versions of the questionnaire were developed. The
first one consisted of an introductory page informing respondents about the
project, the purpose of the survey and providing the confidentiality statement.
The second part of the questionnaire included questions which aimed at gathering
the profile of the respondents (i.e. their position within the company and
contact details), to validate the company details, which were already publicly
available, and identify the relation/involvement of organisations in IoT. The
third section was aimed at measuring the degree to which organisations face the
challenges identified in the literature (academic literature, industry reports,
experts’ insights, web articles etc.). 83 factors referring to legal,
technological, financial, human, knowledge-gap and organisational groups of
barriers were converted into a question format with seven-point Likert scales
with “disagree” – “agree” anchors to measure the degree to which those barriers
apply to companies. The fourth section of the questionnaire was aimed at
identifying the type of support that would help companies overcome barriers. For
collecting feedback on the initial questionnaire, the pilot survey was filled
in by the participants of the Tech Tuesday event (the event organised by
Newcastle University School of Computing, Newcastle University Business School,
Institute of Coding at Newcastle University and the Sphere Network) - the
representatives of IoT-specific companies in the North-East. They accessed the
online version of the questionnaire through a URL. Only two questionnaires were
returned, with the recommendation to simplify the questionnaire.
To address the
comments from piloting the data collection tool, a second version of the survey
was designed. The survey was shortened and simplified
by removing the questions for validating company details as well as the level
of cooperation with other companies from the IoT sector. The questions relating
to barriers and support were simplified in such a way that the need for ranking
specific issues related to each sub-group of legal, technological, financial,
human, knowledge-gap and organisational barriers was eliminated. The shortened
list of barriers was fitted onto one page of the questionnaire to ensure
convenience when filling it in. The
final list of barriers consisted of 19 closed-choice questions and 6 questions
requesting respodents to specify other types of
barriers for each category, if they exist. The respondents had to indicate the
strength to which the company faces each type of barrier on a 7-point Likert
scale between “strongly disagree” to “strongly agree”. The final list of
barriers provided to respondents for ranking and their sources is presented in
Table 1: The list of barriers included in the
Please answer the
questions below based on your experience with the challenges and issues that
your organisation has been facing, while developing and/or deploying IoT
barriers have been significant...
Regulatory issues (e.g.
lack of security standards, lack of liability for failures, lack of legal
(Forum, 2019, Daube, 2019)
Issues with legislative
mechanisms (e.g. partial implementation of IoT related policies, variance in
mechanisms, standards and policies)
(Singh et al., 2015, Meddeb, 2016)
operability issues (e.g. data formats, protocols, interoperability issues,
lack of unified security standards)
(Calvillo et al., 2016, IEEE, 1990, Fan et al.,
2014, Harris et al., 2015, Blackstock and Lea, 2012, Brous and Janssen, 2015)
Service quality issues
(Gerber, 2018, 2019)
(e.g. difficulty to integrate technology, dependence of IoT system on other
(e.g. internet, electricity)
(Perera et al., 2014, Luthra et al., 2018)
Security and privacy
(Carcary et al., 2018, Xing et al., 2013, Lee and
Lee, 2015, Riggins and Wamba, 2015, Haddud et al., 2017, Sahraoui and Bilami,
2015, Xu et al., 2016, Hedge, 2018)
Scalability issues (e.g.
difficulties in adding new machines, nodes and servers, difficulty in
increasing the capacity of existing software and hardware)
(Gupta et al., 2017, Borgia, 2014, H. Dutton, 2014,
Da Xu et al., 2014, Miorandi et al., 2012)
Issues related to
variance in IoT architectures
(Gardašević et al., 2017, Haddud et al., 2017,
Bughin et al., 2015)
Financial Costs (e.g.
high energy usage, long and costly implementation, maintenance and repair
(Sethi and Sarangi, 2017, Pang et al., 2015, Decker et
al., 2008, Lee and Lee, 2015, Haddud et al., 2017, EnterpriseManagement360,
2019, Schroeder et al., 2019)
Financial risks (e.g.
potential project failure, long implementation, disruptions in enterprise
(Reynolds et al., 2018, Joshi, 2018, Charara, 2018)
Need to recruit
(Talavera et al., 2017, Hussain, 2017)
Lack of expertise (e.g.
technical and analytical skills)
(Brous and Janssen, 2015, EnterpriseManagement360, 2019,
Bughin et al., 2015, Yazici, 2014, Harris et al., 2015)
Issues with workforce
structure and workflow (e.g. need for restructuring collaboration units of
organisations, lack of clear workflow)
(SoftwareAG, 2019, Buntz, 2016).
lack of validation and
(Schroeder et al., 2019, Harris et al., 2015,
DataFlair, 2018, Hedge, 2018, Lee and Lee, 2015, Riggins and Wamba, 2015,
Haddud et al., 2017, Talavera et al., 2017)
Lack of information on
(Schroeder et al., 2019, Harris et al., 2015,
DataFlair, 2018, Hedge, 2018, Lee and Lee, 2015, Riggins and Wamba, 2015,
Haddud et al., 2017, Talavera et al., 2017)
(Su et al., 2011, Djahel et al., 2014, Perera et al.,
2014, Kamble et al., 2018)
issues (e.g. lack of clear goals and objectives, lack of strategic insights,
organisational reluctance to change strategy and develop a profit model)
(SoftwareAG, 2019, Haddud et al., 2017).
Lack of appropriate
mechanisms to facilitate collaboration (e.g. regarding sharing data and building
wider collaborations between institutions)
(Moore, 2018, SoftwareAG, 2019)
Data Collection and
Following the pilot
study, the second version of the questionnaire was distributed to the companies
with available email addresses from the updated database of IoT-related
companies. The companies were contacted through emails and requested to fill in
either the questionnaire embedded in the email or the Qualtrics survey
accessible through the link. Additionally, the survey was promoted among the
participants of the IoT North Meetup. IoT North (UK) is a community uniting
people who are interested and involved in the development and the
implementation of IoT in the private and public sectors. The period of data collection
was between February and September 2020. Out of 577 companies, 36 responses
The analysis of the collected data was conducted using SPSS v.25
software, which made it possible to produce descriptive statistics of the responses.
The software was utilised to generate mean and mode values for each question
and histograms, which illustrate the distribution of scores for responses along
the continuum from negative (strongly disagree) to positive (strongly agree)
ranking. Prior to the analysis of the barriers, organisations’ profiles were drawn
in terms of companies’ locations, the type of services/products they provide
and the level of involvement in IoT. The latter characteristic was measured by
the percentage of staff and income related to IoT projects. Second, the degree
to which companies experience legal, technological, financial, human,
knowledge-gap and organisational barriers was analysed using cumulative scores
for each group and scores for separate indicative factors within each group.
Third, the average score of the level of support required for companies to
address the challenges in IoT implementation was calculated.
Results and Analysis
Profile of Companies
The companies are located in 6 regions of the
UK, the South West, South East, West Midlands, North East, North West, Scotland
and Wales (Table 2). The companies offer various types of services and
products, such as: a) software and hardware, b) smart devices (wearable,
indoor, outdoor) c) robotic equipment, d) app and website development, e) IoT
market assessment, f) cloud platforms, g) data analytics and machine learning,
h) IoT network and infrastructure, i) connectivity
and communication devices, j) security-ensuring devices.
Table 2: The location of companies
South East of England
London, Milton Keynes, Newbury, Reading, Woking
Birmingham, Telford, Leamington Spa
North East of England
Blyth, Durham, North Shields, Sheffield, Newcastle, Wakefield,
North West of England
The percentage of employees involved in IoT-related projects and the
percentage of income from IoT-related projects are clustered around the lowest
and highest values of the percentage scale (Figure 1). 18 companies (51.4%) reported that 81-100% of
income comes from IoT-related projects, engaging more than 80% of employees. 17
companies (48,6%) have on average between 1-20 % of income generated by IoT
projects, involving on average between 11 and 20% of company staff.
Figure 1: The involvement in IoT
Figure 2 presents the cumulative scores
for each group of barriers. The histogram demonstrates that on average companies tend neither to agree nor disagree with the existence
of the barriers. Mean scores suggest that 8 companies do not provide a
definitive answer, 12 companies disagree and 16 companies agree that
technological factors challenge the implementation of IoT. While 10 companies
are not certain as to whether the development of IoT is hindered by the legal
framework, 15 companies are inclined to think that there are no legal challenges.
A slightly lower number of companies (11) reported the negative role of legal
factors in IoT projects implementation. Most of the scores for financial
barriers range between “neither agree nor disagree” to “agree”. The surveyed
companies have similar views in relation to the knowledge-gap, whereby 17
respondents acknowledged the challenges attributed to the low awareness of IoT
benefits, 10 companies reported a lack of barriers and 9 companies are
uncertain about the role of the factor. Without taking into account the
responses indicating uncertainty, there are 16 compared to 10 companies that
face organisational management issues hindering IoT project implementation. As
for human barriers, the average score is skewed towards the positive scale,
meaning that most of the surveyed companies do not have adequate human
resources to successfully implement projects.
Figure 2: The frequency distribution of barriers.
The analysis of each factor attributed to the group of barriers provides
a more detailed insight and makes it possible to interpret the scores. For
example, the measurement of legal barriers is made up of three dimensions, as
presented in figure 3. The distribution of scores around the “neither agree nor
disagree” scale is explained by the responses about the existence of other
legal barriers. The majority of respondents are not certain whether other legal
factors slow down the adoption of IoT. Other factors include cross-country
standards about data adequacy and GDPR standards, which make the wider adoption
of IoT technology challenging for organisations. The issues with the regulatory
framework, such as lack of security standards, lack of liability for failures
and lack of legal obligations, concern the least part of companies. There is a proportional number of responses
about the existence vs lack of legal barriers attributed to legislative
mechanisms (e.g. partial implementation of IoT related policies, variance in
mechanisms, standards and policies).
Figure 3: Legal
Figure 4 demonstrates that technological
barriers are comprised of 6 pre-defined factors. In the group of “other”
factors, respondents indicated the challenges with understanding the longevity
of designs, vendors’ reliability and data science predictive capabilities. Mostly,
the companies are not certain which these factors act as obstacles in IoT
implementation. The results suggest that standardisation and operability (e.g.
data formats, protocols, interoperability issues, lack of unified security
standards), security and privacy, variance in IoT infrastructures,
interdependence and service quality issues negatively affect adoption. In
contrast, scalability issues, namely, difficulties in adding new machines,
nodes and servers, difficulty in increasing the capacity of existing software
and hardware, concern fewer companies in the sample.
In the financial group of barriers,
respondents distinguished additional factors, which are the lack of funding for
start-ups and market demand for mass low cost solutions cutting the reliance on
dedicated devices. The scores attributed to these factors explain the companies'
concerns, although no association between them and IoT implementation is
observed (Figure 5). 18 against 10 companies confirmed that high energy usage, long and
costly implementation, maintenance and repair costs act as obstacles slowing
down the adoption of IoT. Potential project failure, long implementation,
disruptions in enterprise operations make the implementation even more
challenging, as expressed by 20 respondents compared to 8 responses indicating
no correlation between incurred financial risks and IoT adoption.
Figure 5: Financial
Figure 6 presents the distribution of responses
in relation to four specific issues contributing to the human barrier group.
Companies highlighted that technophobia, mind-set, inertial and risk-aversive
behaviour may potentially challenge the development and adoption of IoT. 15
against 11 companies believe that the need for restructuring collaboration
units of organisations and workflow are unlikely to be a barrier in IoT
implementation. However, company representatives are inclined to think that IoT
adoption is hindered by a shortage of skills and the need to recruit a specialised
workforce to fill the gap in technical and analytical expertise.
Figure 6: Human
gap group of barriers is measured by the uncertainty of IoT implementation
value, the limited knowledge of operational solutions and other factors, such
as the lack of understanding between hardware and software engineers, lack of
understanding of terminology and jargon (Figure 7). Compared to other groups of
barriers, the difficulty in implementing projects due to a limited awareness of
benefits and functionality is more common among IoT companies. However, most
respondents are uncertain or reject the negative role of “other” barriers, which
affects the cumulative mean for the knowledge-gap factors.
barriers concern platform management, strategy, mechanisms of collaboration and
other factors, such as weak management, client
businesses working in silos, bureaucracy and trust in security policies. Figure
8 demonstrates a similar pattern of attributing either the lowest (“strongly
disagree”) or middle (“neither disagree nor agree”) scores to the “other”
factors. The analysis of the remaining organisational factors shows that the distribution
curve is not well-defined, with slightly higher frequency on the right-hand
side of the scale.
Figure 8: Organisational Barriers
Figure 9 demonstrates
the strength of the need for support in addressing legal, technological,
financial, human, knowledge-gap and organisational barriers. Overall, companies
do not express a strong need for support to overcome challenges. As regards legal
barriers, the common answer was that either a little support or no support at
all is needed. The companies specified that while core business does not need
to be supported, there should be opportunities to grow and innovative product
offerings. The SME framework needs to be developed for the companies in the
North East to facilitate IoT implementation in the region. Against the backdrop
of challenges attributed to technological factors, the companies expressed some
interest in support to overcome technological barriers. Particularly, they need
help in finding good hardware suppliers to work with when developing
applications that require IoT elements. There is a need to develop interfaces
and functionality in devices to strengthen the level of privacy. Also, the companies need a better
infrastructure in terms of the security and reliability of Internet
integration. For scalability purposes, the companies would benefit from full
information and guidance on different technologies, the standardisation of
protocols and functionality in the IIoT space. 25
companies need from a little to a great deal of investment to reduce the financial
burden and eliminate potential risks. Similarly, the majority of companies need
skilled staff and tools to manage human resources to overcome IoT
implementation barriers. Apart from the expressed need for engineers (e.g.
hardware, firmware, data and AI) and workforce having wider skills and experience
to maintain the progress in the field, the companies require support in
conducting special training for existing staff. There is a need for an
independent party to discuss case studies that would facilitate the
cooperation/collaboration between specialised and non-technical employees and
help establish a common language between them. The knowledge gap is a major concern
for companies, which is why 31 out of 36 respondents believe that by increasing
the awareness among corporate customers, the informed decisions would fuel the
implementation of IoT in their organisations. The respondents believe that
local governments need to be educated about the benefits of IoT. The support
would help understand the outcomes of IoT adoption through the wider
explanation of use cases, infrastructural solutions and regulatory frameworks
for major sectors, including Electricity, Oil and Gas, Medicine, Manufacturing
and Retail. A third of the companies responded that they do not need any type
of support to address organisational barriers. However, the companies needing
support would benefit from strengthening their stakeholders’ network.
Figure 9: Need for support
The results of the survey mostly confirm the factors drawn from the
review of the literature. Technical issues are associated with three aspects of
the technological environment. First, the barriers concern the deviation of
formats, standards protocols, architectures and service platforms, which result
in the reduction of efficiency (EuropeanCommission, 2019, Calvillo et al., 2016). Companies resort to the replacement of other technology as a remedy
to increase the efficiency and interoperability of devices (Baños, 2018). Second,
the technicality of IoT devices compromise security and privacy, which
undermine the IoT value proposition (Lee and Lee, 2015, Weinberg et al., 2015, Sahraoui
and Bilami, 2015, Xu and Helal, 2016).
Third, the quality of service enabled by IoT still needs improvement, which is
partially rooted in the quality of infrastructure, such as internet
connectivity and a stable electricity supply (Luthra et al., 2018, Gerber, 2018).
Financial barriers are manifested by the costs
of energy and implementation, potential costs incurred by the long project implementation
and payback, and the lack of investment. Although IoT
technologies are power-efficient (Borgia, 2014), the adoption of devices usually leads to their increased usage and
an increase in electricity consumption accordingly (Sethi and Sarangi, 2017). Secondly, IoT implementation usually takes longer than the
deployment of traditional devices (Charara,
2018). While companies can be
willing to allocate a longer time and investment into IoT projects, it is not
uncommon for the payback to be delayed or projects not to break even at all (Reynolds et al., 2018, Luthra et al., 2018).
Within the human barriers group, the
shortage of skills and specialised workforce scored high, meaning that the lack
of IoT installation and maintenance specialists challenge the deployment and
operation of new technological infrastructure. A successful IoT deployment does
not guarantee value for the company, though, as the potential of the technology
can hardly be realised if employees do not have the skills to operate it (Brous and Janssen, 2015, EnterpriseManagement360,
skills gap can be accounted to salient beliefs, such as limited awareness of the benefits and functionality, technophobia,
inertial and risk-aversive behaviour.
Organisational barriers stem from the
limited capabilities of firms to manage technological resources and build a business
case. For example, poor data management is associated with the inability to
manage multiple platforms supporting IoT devices, which trigger additional
investment of time and money and a decrease of trust towards technology (Wenge et al., 2014). Also, companies can use poor analysis,
strategies and plans on how to monitor and capture value from IoT projects (SoftwareAG, 2019).
Management barriers can be explained by organisational culture, resistance to
new approaches and technologies, as well as scarce knowledge of benefits and
risks (Ferretti and Schiavone, 2016, Valmohammadi, 2016, H.
are some concerns in relation to GDPR standards across countries, the companies
tended to disagree with the statement that a regulatory framework is not
adequate to encourage the development of IoT projects. This can be explained by the measures that
the Government undertook in 2018 by introducing the
Code of Practice for IoT security (Daube, 2019). Previously, security mechanisms were voluntarily embedded in IoT
products. Recently, the Government started enforcing the requirement that all
manufacturers must ensure security in three ways: 1) the provision of unique
IoT device passwords, 2) the compliance of manufacturers with vulnerability
disclosure policy and 3) the provision of explicit information about the
minimum length of time required for security updates (Gov.uk, 2020).
The survey was conducted to give an empirical insight into the factors
challenging the implementation of IoT projects in the UK. The most frequent
answer reflects neither disagreement nor agreement with the statement that
legal, technological, financial, human, knowledge gap and organisational
barriers challenge the adoption of IoT. Other responses suggest that
technological, financial, knowledge gap, human and organisational barriers
exist. Only legal factors were found to be of a lesser concern for the surveyed
sample of organisations. The degree of support needed to overcome barriers
correlates with the degree to which companies experience a particular type of
barrier. From moderate to a great deal of support is required for companies to
cut down the financial costs/risks, fill in the skills and knowledge gap and
amend workforce structures.
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Journal of Information Management, 34, 603-621.