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Citation: Arunnima, B.S.; Bijulal, D.;
Sudhir Kumar, R. Open Innovation
Intellectual Property Risk Maturity
Model: An Approach to Measure
Intellectual Property Risks of
Software Firms Engaged in Open
Innovation. Sustainability 2023,15,
11036. https://doi.org/10.3390/
su151411036
Academic Editors: Fabrizio
D’Ascenzo and Ja-Shen Chen
Received: 12 April 2023
Revised: 29 June 2023
Accepted: 8 July 2023
Published: 14 July 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
sustainability
Article
Open Innovation Intellectual Property Risk Maturity Model:
An Approach to Measure Intellectual Property Risks of
Software Firms Engaged in Open Innovation
B. Senakumari Arunnima 1,* , Dharmaseelan Bijulal 2and R. Sudhir Kumar 3
1College of Engineering Trivandrum, APJ Abdul Kalam Technological University,
Thiruvananthapuram 695016, India
2Government Engineering College, Barton Hill, APJ Abdul Kalam Technological University,
Thiruvananthapuram 695035, India; bijulal.d@gecbh.ac.in
3
NSS College of Engineering Palakkad, APJ Abdul Kalam Technological University, Akathethara 678008, India;
sudhirdak@gmail.com
*Correspondence: arunnimabs76@gmail.com; Tel.: +91-9846-960-754
Abstract:
Open innovation (OI) is key to sustainable product development and is increasingly
gaining significance as the preferred model of innovation across industries. When compared to closed
innovation, the protection of intellectual property (IP) that is created in open innovation is complex.
For organisations engaging in OI, a sound IP management policy focusing on IP risk reduction plays
a significant role in ensuring their sustained growth. Assessing the risks that are involved in IP
management will enable firms to devise appropriate IP management strategies, which would ensure
sufficient protection of an IP that is created in an OI model. Studies indicate that the risks which are
associated with IP and risk management processes also vary with company segments that range from
start-ups to micro, small, medium, and large organisations. This paper proposes an open innovation
IP risk assessment model to compute the open innovation intellectual property risk score (OIIPRS) by
employing an analytic hierarchy process. The OIIPRS indicates the IP risk levels of an organisation
when it engages in open innovation with other organisations. The factors contributing to IP risk are
identified and further classified as configurable IP risk factors, and the impact of these factors for the
various company segments is also factored in when computing the OIIPRS. Further, an OI IP risk
maturity model (OIIPRMM) is proposed. This model depicts the IP risk maturity of organisations
based on the computed OIIPRS on an IP risk continuum, which categorises firms into five levels of IP
risk maturity. The software firms can make use of the OIIPRMM to assess the level of IP risk and
adopt proactive IP protection mechanisms while collaborating with other organisations.
Keywords:
open innovation intellectual property risk score; open innovation intellectual property
risk maturity; open innovation; intellectual property risks; IP risk management; analytic hierarchy
process; conceptual model
1. Introduction
Innovation is the catalyst in the growth and success of any business. Innovative
businesses create more efficient work processes and achieve better productivity and per-
formance than do their peers. Innovating in a business can conserve time and money and
render a competitive advantage that grows the business in the marketplace [
1
–
5
]. Continu-
ous innovation is critical for creating repeated success for sustainable product development.
Different classifications for innovation exist based on the scope of the innovation, the
actors who are involved in the innovation, the product of the innovation, etc. [
6
,
7
]. One of
the most widely used classifications is that which is based on the parties that are involved
in the innovation process [
8
]: (i) closed innovation and (ii) open innovation. Innovation
within a firm without any transfer of knowledge from external sources or involvement
Sustainability 2023,15, 11036. https://doi.org/10.3390/su151411036 https://www.mdpi.com/journal/sustainability
Sustainability 2023,15, 11036 2 of 19
from external parties is known as closed innovation. Until the year 2000, companies used
closed innovation approaches by restricting innovation to within the organisations [
8
].
However, in the early 2000s, firms started collaborating with external parties such as
customers, suppliers, consultants, universities, and competitors to co-create products and
services. Such collaborative efforts with external parties created a new business model,
which is known as ‘open innovation’. Ref. Chesbrough
[8]
, who coined the term open
innovation (OI), defined it as the use of purposive inflows and outflows of knowledge
to accelerate internal innovation, and expand the markets for external use of innovation,
respectively. The business model of OI is gaining popularity across all industrial segments.
Studies indicate that adopting OI business models enables the growth of the business, and
it fosters a culture of innovation [
9
]. However, there is a growing concern about protecting
intellectual assets and potential value-sharing amongst collaborating firms when they open
up to OI [10].
Several studies emphasise the significance of the protecting of IP in an OI setting.
Much of the research on OI is related to the effect of OI on a firm’s performance. Among
them, a large amount of the research is focused on the manufacturing, pharma, and
telecommunication industries. In the software industry, OI is gaining traction; however,
studies that focus on OI and studies that assess the level of IP risk in OI are limited.
This research aims to analyse and identify the various factors that contribute to an
organisation’s IP risk while engaging in OI. This paper proposes a model to assess the
varying levels of IP risk across company segments such as start-ups, micro, small, medium,
and large organisations in the software industry. A tool that aids organisations in assessing
and measuring IP risk enables them to manage and protect their IP better. Further, following
the capability maturity model and risk management maturity model, an OI IP risk maturity
model is proposed. This model presents the IP risk score of a firm with varying levels of
maturity in IP risk management. Assessing the levels of IP risk and understanding the
organisation’s position based on the IP risk score enables organisations to devise strategies
to lower IP risk and protect their assets as they collaborate with other organisations and
co-create products and services.
The related theoretical background, which covers the significance of IP management
in OI and the factors that contribute to the IP risk of organisations that engage in OI, is
discussed in Section 2.1 under Section 2. The objectives of this study and its methodology,
the configurable risk factors for better IP protection, the model for IP risk assessment,
and the IP risk maturity model are then discussed. The results of this study, including
the varying levels of IP risk score across various company segments, are subsequently
discussed selecting Fintech firms from India. Further, how the insights that are gained
by measuring the level of IP risk in OI would benefit the firm and the stakeholders when
this proposed model is used is discussed in the Conclusions section. The scope for future
research in IP management in OI is also discussed.
2. Materials and Methods
The theoretical background, research gaps, and the methodology adopted for this
research work are discussed in this section. Further, the models proposed as part of this
study are discussed.
2.1. Literature Review
The management of IP and the enforcement of rights play a crucial role in protecting
the rights of innovators [
11
]. The need for IP management in OI has been researched by
several scholars. The literature review in this paper is organised into four sections. In
Section 2.1.1, the need for and the significance of IP management in OI are discussed.
OI in the software industry is then discussed in Section 2.1.2 and the factors that lead to
IP risk while engaging in OI are discussed in Section 2.1.3. Research gaps are discussed
subsequently in Section 2.1.4.
Sustainability 2023,15, 11036 3 of 19
2.1.1. IP Management in OI
Although OI is on the rise, the level of IP filing has not declined [
12
]. The worldwide
filing of patents increased by 3.6%, with 3.4 million patent applications, and trademarks by
5.5%, with 18.1 million trademark applications in 2021. Asia emerged as the hub for global
IP filing activity, with China topping the list at 1.58 million patent filings (an increase of
5.9%) and 9.45 million trademark filings (an increase of 1.2%). India filed 61,573 patents (an
increase of 8.5%) and 488,526 trademark applications (an increase of 15.1%) in 2021.
Several researchers have established the need for IP protection in OI [
10
,
13
–
25
]. The
significance of IP protection in an OI setting is also emphasised in several studies. A study
conducted amongst Swedish manufacturing firms found that firms consider it more critical
to patent when they are engaged in OI than in closed innovation [
17
]. In the UK, nearly
90% of firms that are active in OI regard patents as an essential method to signal the nature
of their technological capabilities [
22
]. A study which was conducted in the Middle East
and in Europe established that firms engaging in OI would be involved in IP assignment
and acquisition activities [10].
Firms that view IP as an opportunity to create value and build the innovation ecosys-
tem consider IP as an enabler for OI [
25
,
26
]. The protecting of IP enables inter-organisational
innovation processes by protecting the rights of collaborating firms [
15
,
27
–
29
]. A rise in
the strength of IP protection in OI enables free sharing and dissemination of technological
information. It also promotes various forms of technology trade [
18
,
30
]. Therefore, OI
communities and commercial firms have a reason to use the IPR institution in place to
protect their innovation systems [15].
While strong levels of IP protection do stifle OI, in the absence of this protection firms
may resort to secrecy [
31
] to protect their innovation. This is a situation that not only
hinders OI but negates it [
10
]. However, the protection of IP in OI is complex due to many
factors such as (i) the existence of several business models for collaboration and subsequent
revenue generation/sharing, (ii) the involvement of external actors in the OI ecosystem,
(iii) a lack of proper policies that govern the OI model, (iv) differences in the existing
laws that offer protection in case of cross-border collaboration, and (v) the associated
complexities in managing and enforcing IP rights [10,13,25,26,32,33].
2.1.2. OI in the Software Industry
Much of the research conducted in OI that is related to IP management is generic.
However, certain research works have focused on specific requirements for the manufac-
turing [
17
], pharmaceutical [
10
], and telecommunications industries [
33
]. In the software
industry, for instance, innovation tends to be highly incremental and cumulative, in which
case essential licensing to use an innovation is more likely to involve many patents [
15
].
Due to the specific needs of IP protection in the software industry, this research focuses on
the software industry, specifically, the financial technology industry, in which the largest
extent of OI currently occurs [34].
Financial technology firms, also known as FinTechs, which is an umbrella term that
is used to describe innovative technology-enabled financial services business models,
are inducing a paradigmatic shift in the manner in which financial service firms deliver
pecuniary and non-pecuniary benefits to interacting parties. FinTech covers areas such as
banking, insurance, loans, personal finance, electronic payments, and wealth management
of retail and corporate customers. The total global FinTech investment recorded was USD
164.1 billion in 2022, with 6,006 sales deals [
35
]. The global financial sector is expected to be
worth USD 161.2 billion by 2027 [36].
With an estimated market opportunity of USD 1.3 trillion by 2025, the Indian FinTech
ecosystem has emerged as a formidable global force [
37
]. Following the US and the UK,
India is the third largest FinTech market. India’s total FinTech funding in 2021 was USD
7.8 billion. India is considered advanced in FinTech/third party ecosystems, and it has
an open banking readiness index of 6.1. The open banking readiness index provides a
framework for banks to assess their open banking capabilities. It is defined based on
Sustainability 2023,15, 11036 4 of 19
five dimensions—adoption of APIs, FinTech/third party ecosystem, state of data-based
transformation, data monetisation, and state of innovation. It is measured on a scale of 0 to
10, with 0 being the lowest and 10 being the highest score [
38
]. The Indian FinTech market
is expected to grow at a compound annual growth rate (CAGR) of 31% till 2025 [
39
,
40
].
With FinTech and traditional players working together, a greater potential is unlocked.
Thus, OI is the key to growth for FinTechs and banks.
A total of 10,662 patents were awarded to 116 FinTech firms across the world in
2016. The average is around 92 patents per FinTech firm per year [
34
]. In 2018, financial
technology accounted for nearly 4000 FinTech patent applications owned by some of
the largest institutions in the technology and financial sectors such as Bank of America,
Google, IBM, and Visa [
41
]. This level of patenting activity renders the financial technology
industry a high innovation industry. FinTech OI is on the rise, as indicated in several
research reports [37,42–46].
2.1.3. Open Innovation Intellectual Property Risk Factors
While multiple firms collaborate to produce a new product or service, the obvious ques-
tion would be on who will own the IP created as a result of OI. Sound management of IP
would require the identification of factors that lead to IP-related risks. Several factors influence
the IP risk of a firm in an OI setting. While some firms rely on contractual agreements and
formal methods for IP management in OI, which may lower the risks, other firms employ
informal methods, which may substantially increase the risks [
33
,
47
]. The management of
IP is largely trust-based in some cases, especially in start-ups and micro/small firms
[48,49]
.
According to the available literature, thirteen distinct factors can influence the risks in IP
management when an organisation engages in OI. These factors (Table 1) are: (i) IP manage-
ment style—formal/informal [
22
,
33
,
47
]; (ii) contracts—non-compete/nondisclosure/other
contractual agreements
[22,33,47]
; (iii) licensing model—exclusive/non-exclusive/ IP ac-
quisition/IP transfer
[10,15,17,18]
; (iv) IP forms—patents/trademarks/copyright/trade
secret
[17,24,50–52]
; (v) business/revenue model—revenue sharing/referral /others [
17
,
25
];
(vi) firm size (turn over) [
53
] ; (vii) stage of the firm—start-up to maturity [
48
]; (viii) col-
laborating stage [
54
] ; (ix) platform strategy [
33
,
38
]; (x) OI type—amongst firms/firms,
universities/firms, and individuals (crowd sourcing) [
26
,
33
,
55
]; (xi) product types—business-
to-business/business-to-consumer/business-to-government [
49
]; (xii) IP risk assessment and
governance procedures [
56
]; and (xiii) cross-border OI [
24
]. While factors that can cause risk
in IP management are identified, these factors are not being further utilised to assess the level
of IP risk in collaborating organisations.
2.1.4. Research Gaps
Several researchers have studied the influence of IP management policies and organ-
isational strategies on the performance of a firm while it engages in OI [
7
,
13
,
17
,
25
,
33
,
57
].
Sound IP management is crucial to protect the intellectual assets of organisations that are
involved in OI. A key aspect of a sound IP management policy would be on how IP risk
is identified and managed. Studies indicate that proactive risk management is beneficial
for projects as it increases the predictability of outcomes [
58
–
60
]. Standardisation of risk
identification and reporting are important [
60
], and a well developed risk awareness model
ensures mitigation methods are identified and executed in a timely manner thereby reduc-
ing risk [
59
,
61
]. For effective risk management, the factors that contribute to IP risk in OI
should be identified and assessed. However, there is no evidence for the use of IP risk
assessment models in OI. There does not exist a ‘one-size-fits-all’ approach when dealing
with IP risk management across firms. A tool that can simply and intuitively measure the
various risk factors uniformly across various segments, such as start-ups, micro, small,
medium, and large organisations is required [
62
,
63
]. In this context, the current study
aims to define a new approach to IP risk assessment for firms that are engaged in OI in
the software industry. As the FinTech industry is identified as the most innovative in the
software industry, this study focuses on FinTechs in India.
Sustainability 2023,15, 11036 5 of 19
2.2. Open Innovation Intellectual Property Risk Management
In the software industry, OI is a multidimensional and complex activity. A unified
approach to IP risk assessment for various company segments such as start-ups, micro,
small, medium, and large organisations is required to ensure sufficient protection of the
intellectual assets of collaborating parties. The objectives of the study, the methodology, and
the risk factors that contribute to IP risk, which can be configured to reduce the IP risk levels,
are discussed, followed by an approach to OI IP risk assessment in the software industry.
2.2.1. Objectives
The first objective of this study is to define a model to assess the level of IP risk of
organisations that engage in OI. To propose an OI IP risk assessment model, the key factors
that can be configured to adjust the risk levels of an organisation are identified. Once
these factors are identified, guidelines to assess these risk factors are defined so that all
software firms follow the same guidelines for IP risk assessment. Further, a method to
compute an open innovation intellectual property risk score (OIIPRS) based on these risk
factors is proposed. The second objective of this study is to establish an open innovation
intellectual property risk maturity model (OIIPRMM) that can depict the IP risk maturity
of an organisation on the basis of varying levels of IP risk. The scope of this study is limited
to the software industry and FinTechs in particular.
2.2.2. Methodology
The research work is carried out in four stages (Figure 1). The first stage of the research
aims to identify factors that contribute to IP management risk in firms that are engaged in
OI. From thirteen different factors identified from the existing literature, five factors that can
be configured to reduce IP risk are determined in consultation with industry experts. The
details of how to determine the five configurable factors from the thirteen different factors
are discussed in subsequent sections. The second stage of this study focuses on developing a
risk score that is based on these identified factors. For this, industry experts are consulted to
perform a pairwise comparison of the factors by using the analytic hierarchy process online
system (AHP-OS) [
64
]. The factors are compared pairwise for different company segments
such as micro, small, medium, large, and start-ups [
62
,
63
,
65
], because the significance of
these factors varies with the company segment. The resulting pairwise comparison matrix
of the risk factors is fed into an AHP program that is written in the R software to compute
the risk factor weighting for each company segment.
In the third stage, an online survey is employed to gather the risk factor scores of each
identified risk factor from the organisations that are involved in OI. This study focuses on
FinTechs in India that are engaged in OI. The OIIPRS of the organisation is then computed
from the risk factor score that is provided by the organisation and the risk factor weighting
that is established by using the AHP previously. The fourth stage of this study aims at
establishing an open innovation intellectual property risk maturity model. This model
depicts the IP risk maturity of organisations based on the computed OIIPRS on an IP risk
continuum, with five levels of maturity, similar to the capability maturity model [
66
], the
innovation maturity model [
26
,
67
,
68
], and the risk management maturity model [
69
–
71
].
The OIIPRMM helps organisations assess the level of IP risk and the extent of their maturity
in IP risk management while engaging in OI.
Sustainability 2023,15, 11036 6 of 19
Figure 1. Methodology.
Ten IP management experts from the software industry are consulted to compute the
intellectual property risk factor weights by using an analytic hierarchy process. Using
random sampling, around 250 FinTechs that are headquartered in India or have a presence
in India are surveyed to assess the OIIPRS. A list of FinTechs in India was identified
based on several industry reports [
37
,
72
–
74
] and internet-based information. A senior
executive from each of these identified firms was contacted to gather the targeted feedback
by employing an online survey. Around 675 FinTechs were contacted from June 2022 to
December 2022, out of which we received responses from 250 FinTechs. The chosen firms
are sampled from different company segments such as micro, small, medium, and large
organisations, and start-ups. The survey respondents include CXOs, product managers,
and senior managers who are responsible for the innovation activities of the selected firms.
2.2.3. Configurable Intellectual Property Risk Factors
Several factors contribute to the risk that is related to IP in an OI setting. These factors
can be broadly categorised as configurable and non-configurable factors, based on whether
the factor can be configured to reduce the IP risk level of the organisation. Factors such as
the size of the firm (turnover), the stage of the firm (start-up to mature organisations), the
type of OI employed, the type of product developed, etc., cannot be altered; hence, they are
non-configurable risk factors. The style of IP management (formal/informal), the contracts
employed (nondisclosure agreements, IP ownership agreements, etc.), the licensing model
(exclusive licensing, non-exclusive licensing, IP acquisition), IP risk assessment and the
governance procedures followed, and whether the organisation is involved in cross-border
open innovation can be configured to reduce the IP risk levels; hence, they are categorised
as configurable risk factors.
The OI IP risk score and the maturity model are developed based on the configurable
risk factors. The overall risk factors that are identified during the literature review are
categorised as configurable and non-configurable in consultation with industry experts.
Table 1provides the list of IP risk factors, indicating whether they are configurable or
non-configurable to vary the IP risk levels.
Sustainability 2023,15, 11036 7 of 19
Table 1. Configurable/non-configurable IP risk factors.
Sl. No. Factors Configurable Reason for Configurability
1 IP management style—formal/informal Yes
Companies can implement formal IP manage-
ment policies, thereby reducing IP risk
2
Contracts—non-compete/nondisclosure/
other contractual agreements Yes
Sound legal agreements play a critical role in
reducing IP risk
3
Licensing model—exclusive/non-exclusive/
IP acquisition/IP transfer Yes
Appropriate licensing strategies can lower
the IP risk
4
IP forms—patents/trademarks/copyright/
trade secret No
While IP forms will influence the IP risk score,
it is not a configurable option available to
companies as each IP form is specific to the
subject under consideration for IP protection
5
Business/revenue model—revenue shar-
ing/referral/others No
Revenue model agreed upon between the col-
laborating parties shall be grouped under li-
censing model and hence not required to be
considered separately
6 Firm size (turn over) No
Size of the firm cannot be adjusted to lower
the IP risk
7 Stage of the firm—start-up to mature No
The stage in which the firm is currently can-
not be adjusted
8 Collaborating stage No
The stage in which the firm opts for collabo-
ration cannot be adjusted
9 Platform strategy No
Not all participating firms will have a plat-
form strategy
10
OI type—among firms, between firms and
universities, between firms and individuals
(crowd sourcing )
No Not a configurable option for firms
11
Product types—business-to-business, business
-to-customer, business-to-government No
Not a configurable option for companies, and
may not have a direct impact on IP
12 IP risk assessment and governance procedures Yes
Risk assessment method, risk management
procedures, and policy governance can influ-
ence IP risk
13 Cross-border OI Yes
Depends on the firm´s strategy and extra mea-
sures can be employed for IP protection and
hence configurable
2.2.4. Open Innovation Intellectual Property Risk Assessment Model
Understanding the IP management risks when a firm engages in OI with another party
will help the firm to devise appropriate strategies to lower the risk, which will protect their
IP. In this context, a model to assess the risks that are associated with managing IP while
engaging in OI is proposed. The OI intellectual property risk assessment model attempts to
assess the risk levels of IP risk factors and compute a score to indicate the IP risk level of
a firm. The risk score, termed as OIIPRS, indicates the risk level of organisations that are
involved in OI, specifically in the context of managing IP that originates from the OI. A
higher OIIPRS indicates that high risk is associated with IP management, and it signals to
organisations to implement necessary controls to lower the risk levels.
The risk factors that are configurable are assigned weights by employing the AHP
[75–83]
,
which is one of the most commonly used multi-criteria decision-making (MCDM) methods
for computing weights of factors involved in decision making. MCDM [
81
,
84
–
87
] is used
when a decision involves taking multiple criteria into account in order to rank or choose
between the alternatives. In situations where multiple factors contribute to an outcome,
MCDM offers processes to assign weights to the criteria, signifying each criterion’s contri-
Sustainability 2023,15, 11036 8 of 19
bution to the outcome. AHP [
82
] is a widely used method of MCDM to assign weights to
the factors involved, particularly for cases that use qualitative data [
83
]. The AHP model
employs a pairwise comparison of the risk factors by industry experts to arrive at the
weight of the risk factors. A three-step process is employed to compute the weights of
the factors. First, a goal–criteria–sub-criteria hierarchy is established for the AHP analysis
(Figure 2). The goal of the AHP analysis in this study is to compute the weight of IP risk
factors in OI. The criteria include the five configurable IP risk factors that were identified in
consultation with industry experts. The various values that are possible for each of the IP
risk factors constitute the sub-criteria.
Figure 2. IP risk factors—AHP model.
Second, intellectual property industry experts are consulted to perform a pairwise
comparison of the IP risk factors by using an AHP-OS [
64
], an AHP-based online system.
In this stage, each IP risk factor is compared to provide the comparative importance of each
factor against the other factors. Saaty’s scale [
75
] is used to perform a pairwise comparison
of the IP risk factors. In the AHP, the consistency of the expert judgements is assessed
using a consistency ratio (CR). A pairwise comparison matrix is said to be consistent if
the consistency ratio of the matrix is less than 10%. The AHP-OS gives a visual indicator
of the comparisons that cause inconsistency, which makes it easier for the experts to
review the comparisons and render them consistent. Industry experts perform the pairwise
comparison of the IP risk factors for each of the company segments (micro, small, medium,
large, and start-up). Third, the pairwise comparison is fed into a software program that is
written in the R language to compute the weight of each of the configurable IP risk factors.
The ahpsurvey package [
88
] provides a consistent methodology for researchers to reformat
data and run AHP on data that are formatted using the survey entry mode.The risk factor
weights that are computed by the R program for each company segment are depicted in
Table 2.
An open innovation intellectual property risk assessment model that is based on a
spreadsheet-based tool (Table 3) is provided to FinTechs to determine the risk factor score
against each IP risk factor. On selecting the company segment, the risk factor weights, which
are computed using the AHP analysis as applicable for the selected company segment, auto-
populate in the tool. On selecting the appropriate response from the options provided against
each assessment question, the risk factor score also auto-populates, based on the guidelines
Sustainability 2023,15, 11036 9 of 19
provided (Table 4). The weighted risk score is computed by multiplying the risk factor weight
and the risk factor score against each risk factor. The sum of the weighted risk scores yields the
OIIPRS of the firm. A sample computation of the OIIPRS of a start-up is depicted in
Figure 3.
Table 2. IP risk factor weights for various company segments.
Configurable IP
Risk Factor Micro Small Medium Large Start-up
IP management style 13.543 16.247 24.623 24.347 15.819
Contracts 37.49 34.789 29.343 29.625 40.281
Licensing model 23.442 23.68 18.369 15.097 20.872
IP policy/governance 15.326 14.76 16.77 17.567 12.886
Cross-border OI 10.2 10.525 10.895 13.365 10.142
For this research, the chosen FinTechs, which are headquartered in India or have a
meaningful presence in India, were given the OI IP risk assessment tool. These firms were
required to rate each of the questions corresponding to the configurable IP risk factors,
based on the guidelines given in the tool. A total of 250 firms responded with their IP risk
assessment. The computed total score, that is, the OIIPRS, was calculated automatically by
the OI IP risk assessment tool. The OIIPRS can range from 100 to 500. If an organisation
gave a rating of 1 to all the IP risk factors, the OIIPRS would be 100, which indicated a
lower level of IP risk. If an organisation gave a rating of 5 to all the IP risk factors, the
OIIPRS would be around 500, which indicated a higher level of IP risk.
Table 3. Open innovation intellectual property risk assessment model.
Open Innovation Intellectual Property Risk Assessment Model
Instructions:
1. Select the company segment as applicable for your company from the dropdown values.
2. On selecting the company segment, the risk factor weight will auto-populate.
3. Select responses for each of the assessment questions from the options provided as dropdown values.
4. On selecting the response, the risk factor score will auto-populate.
5. The weighted risk score and the open innovation intellectual property risk score will be computed automatically.
Select the Company Segment Micro: Investment of less than Rs. 1 Cr and Turnover of less than Rs. 5 Cr
Small: Investment between Rs. 1–10 Cr and Turnover of between Rs. 5–50 Cr
Medium: Investment between Rs. 10–50 Cr and Turnover of between Rs. 50–200 Cr
Large: Investment of greater than Rs. 50 Cr and Turnover of greater than Rs. 200 Cr
Start-ups: Turnover of less than Rs. 25 Cr and years since establishment is less than 7 years
Sl.No Assessment Question Select response from the options provided
Risk
factor
weight
Risk
factor
score
Weighted
risk score
1
Please specify the method of IP manage-
ment and protection followed in your or-
ganisation when it engages in open inno-
vation
Yes, we have formal methods of IP management
and IP protection (Score: 1)
We have a basic framework for IP management
and IP protection (Score: 3)
No, we do not have formal methods of IP manage-
ment and IP protection (Score: 5)
2
Please specify the types of agreements
employed to protect intellectual property
while engaging in open innovation with
external parties?
IP Ownership Agreement [Agreement on who
owns the IP that originates from open innovation]
(Score: 1)
IP Appropriation Agreement [Agreement on how
the revenue sharing is performed for the IP that
originates from open innovation] (Score: 2)
Non-Compete Agreement [Agreement not to
compete with organisations with similar prod-
ucts/domain] (Score: 3)
Nondisclosure Agreement [Agreement not to dis-
close to other parties the details of a product that
originates from open innovation] (Score: 4)
Other Contractual Terms [Any other contractual
term that does not cover the above] (Score: 4)
Mostly trust-based (Score: 5)
Sustainability 2023,15, 11036 10 of 19
Table 3. Cont.
Open Innovation Intellectual Property Risk Assessment Model
3
What is your organisation’s pre-
ferred model for licensing while
engaging in open innovation?
Acquire IP—Our organisation owns the IP that origi-
nates from open innovation (Score: 1)
Transfer IP: Our organisation transfers the IP to the col-
laborating firm (Score: 1)
Exclusive Licensing: Our organisation enters into an ex-
clusive licensing agreement with the collaborating firm,
and will not share the work with anyone else (Score: 3)
Non-Exclusive Licensing: Our organisation can licence
the IP to other organisations as well (Score: 5)
4
Does your organisation have a
well-established IP risk assess-
ment methodology and IP policy
governance mechanism in place?
Yes, we have a formal IP policy governance and IP risk
assessment mechanism (Score: 1)
We have a very basic mechanism for IP policy gover-
nance and IP risk assessment (Score: 3)
No, we do not have a formal IP policy governance and
IP risk assessment mechanism (Score: 5)
5
Does your organisation engage
in cross-border open innovation
? [Meaning, do you collaborate
with firms from other countries
for open innovation]
No, we do not engage in open innovation with organisa-
tions in other countries (Score: 1)
Yes, we engage in open innovation with organisations in
other countries (Score: 5)
Open Innovation Intellectual Property Risk Score (OIIPRS)
Table 4. Guidelines to score IP risk factors.
IP Risk Factors and Options Risk Level Risk Factor Score
IP management style
Formal methods of IP management and IP protection Low 1
Have a basic framework for IP management and IP protection Medium 3
Informal methods of IP management and IP protection High 5
Contracts
IP ownership agreement (agreement on who owns the IP originating from open innovation) Low 1
IP appropriation agreement (agreement on how is the revenue shared for the IP originating from
open innovation) Low 2
Non-compete agreement (agreement not to compete with organisations with similar
products/domain) Medium 3
Nondisclosure agreement (not to disclose the details of product originating from open innovation
to other parties) High 4
Other contractual terms (any other contractual terms that do not cover the above) High 4
No formal agreements (m)ostly trust-based) High 5
Licensing Model
Acquire IP—organisation owns the IP originating from open innovation Low 1
Transfer IP—organisation transfers the IP to the collaborating firm Low 1
Exclusive licensing—organisation enters into an exclusive license with the collaborating firm, and
would not share the work with anyone else Medium 3
Non-exclusive licensing—organisation can license the IP to other organisations as well High 5
IP Policy Governance
Formal IP policy governance and IP risk assessment mechanism Low 1
Have a very basic mechanism for IP policy governance and IP risk assessment Medium 3
No formal IP policy governance and IP risk assessment mechanism High 5
Cross-border open innovation
Do not engage in open innovation with organisations in other countries Low 1
Engage in open innovation with organisations in other countries High 5
Sustainability 2023,15, 11036 11 of 19
Figure 3. OIIPRS—sample for a start-up segment firm.
3. Results
Regular risk assessment of IP while engaging in OI enables organisations to protect
their intellectual assets. The OI IP risk assessment model allows organisations to measure
the level of IP risk that is involved in open innovation by computing the OIIPRS. Organ-
isations can analyse the weighted score of each IP risk factor to identify areas of focus.
Such an analysis would enable organisations to devise appropriate strategies to improve
their overall IP protection mechanisms and reduce risk. Based on the OIIPRS, an OI IP
risk maturity model is designed along the lines of the risk management maturity model,
which enables organisations to assess their current maturity levels and propose targets for
reduced risk levels.
3.1. Open Innovation Intellectual Property Risk Maturity Model (OIIPRMM)
The OI IP risk maturity model (Figure 4) depicts the risk maturity of organisations that
are engaged in OI, and the characteristics of an organisation on an IP risk score continuum.
The maturity model categorises firms into five segments, based on the OIIPRS. Such a
maturity model helps firms to assess the level of IP risk and the extent of their maturity in
their IP risk management while engaging in OI. It also equips them to devise appropriate
strategies to reduce risk levels. Based on the OIIPRS, that ranges from 100 to 500, five
levels of IP risk maturity are defined: (i) level 1, initial; (ii) level 2, developing; (iii) level 3,
established; (iv) level 4, advanced; and (v) level 5, optimised.
Sustainability 2023,15, 11036 12 of 19
Figure 4. Open innovation intellectual property risk maturity model (OIIPRMM).
Initial: Firms that have a very high OIIPRS, ranging from 450 to 500, fall under the
‘initial’ category. Such firms have informal IP risk management practices and IP risk are not
assessed or monitored. They do not possess IP risk assessment system/tools and have no
governance mechanisms for IP risk management.
Developing: Firms that have a high OIIPRS, ranging from 350 to 450, are grouped
under the category, ‘developing’. They have informal IP management practices and rudi-
mentary risk assessment processes. Although they have devised monitoring mechanisms,
these are not regular. They have no IP risk assessment tools/systems.
Established: Firms that have a medium OIIPRS, ranging from 250 to 350, fall under
this category. They have partially formal IP management. They have documented risk
management processes and planned IP risk assessments that are performed periodically.
They follow manual processes for risk monitoring and tracking.
Advanced: Firms that have a low OIIPRS, ranging from 150 to 250, fall under this
category. They have formal IP management and risk management processes integrated with
each stage of OI. The IP risk is assessed regularly, and dynamic dashboards that indicate the
risk and the associated information are made available department-wise in the organisation.
Such firms also have semi-automated IP risk assessment and monitoring procedures.
Optimised: Firms that have a very low OIIPRS, ranging from 100 to 150, fall into the
‘optimised’ category. They have formal IP management and risk management practices
that are focused on the firm’s repeated success. Lessons that are learnt from previous OI en-
gagements are continuously incorporated into risk management processes and procedures.
Their IP risk is assessed regularly, and dynamic dashboards that indicate the risk and the
associated information at the organisational level are made available. Such firms also have
established automated systems for IP risk assessment and monitoring and depend less
on individuals.
3.2. Open Innovation Intellectual Property Risk Assessment Results
Of the 250 FinTechs that took part in the OI intellectual property risk assessment study,
180 FinTechs practised OI, while 70 FinTechs did not engage in OI. Of the 180 FinTechs
carrying out OI, 32% were large firms, 27% belonged to medium-sized companies, 16%
Sustainability 2023,15, 11036 13 of 19
were small companies, 9% were micro-enterprises, and 16% were start-ups. The lowest
OIIPRS score was 100, and the highest was 471. The distribution of the OIIPRS across the
various company segments is captured in Table 5and Figure 5. The corresponding box
plot is depicted in Figure 6. Though the large firms show a comparatively higher range for
the OIIPRS, the majority of the firms have risk scores below 350, indicating that they have
scope to reduce their risk score levels.
Table 5. OIIPRS distribution.
Company
Segment
Minimum
OIIPRS
Maximum
OIIPRS Average OIIPRS Range
Large 100.001 421.686 217.656 321.685
Medium 143.58 470.657 316.376 327.077
Small 159.041 465.216 340.041 306.175
Micro 293.767 462.515 382.406 168.748
Start-ups 140.568 428.081 319.932 287.513
Figure 5. Open innovation intellectual property risk score—absolute comparison.
In the aspect of maturity, 69% of large firms are in the advanced stage of IP risk maturity.
No large firms are in the initial category. This observation coincides with the general
practice of most large firms of having well-defined processes for IP management and, thus,
a lower OIIPRS. However, only 3% of large firms are in the optimised category, possibly
owing to the difficulties in standardising practices across departments. Interestingly, none
of the start-ups are in the initial category, which is contrary to the belief that start-ups
follow ad hoc processes. A significant number of medium, small, and micro segment firms,
and start-ups belonged to the developing or established category with a medium to high
OIIPRS indicating that there is larger scope for these firms to develop better IP management
strategies and reduce IP risk levels. Very few firms were in the optimised category across
all company segments, confirming that more focused efforts are required in reducing IP
risk when firms engage in OI.
Sustainability 2023,15, 11036 14 of 19
Figure 6. Open innovation intellectual property risk score—box plot.
4. Conclusions
This research work contributes to the project management and open innovation lit-
erature. The open innovation intellectual property risk assessment model proposed in
this article contributes to the risk management practices in project management. The
open innovation intellectual property risk maturity model provides an opportunity for
project managers to review the IP risk and devise appropriate strategies to reduce the
IP risk. This article also significantly contributes to the IP management literature that is
related to OI. The open innovation intellectual property risk assessment model presents a
unified approach to the quantitative measurement of the level of IP risk in organisations
that engage in OI. The simple, user-friendly, spreadsheet-based assessment renders the
independent administering of the assessment by organisations effortless. The analytic
hierarchy process, which is a robust multi-criteria decision-making method that is used
to compute the IP risk factor weights, establishes the integrity of the assessment model.
The assessment procedure is standardised by establishing guidelines, which renders the
OIIPRS comparable across organisations.
The open innovation intellectual property risk maturity model categorises firms into
five levels of IP risk maturity based on the OIIPRS. The IP risk maturity of organisations
can be assessed by the OIIPRMM when it is used as a benchmarking tool. Consulting
organisations can employ the OIIPRMM to assess the IP risk maturity of organisations and
compare the maturity levels of organisations that operate in a given functional domain.
Such assessments, which are made by consulting organisations, enable the organisations
that engage in OI to compare their competitive positions in terms of IP risk management
practices. In addition, it allows organisations to strengthen their processes to ensure risk
reduction for innovation projects’ success and in turn better IP protection. The IP polices of
an organisation plays a key role in the organisation’s performance and enable sustained
growth, and IP risk reduction measures form a crucial part of IP policies. Additionally,
to enable investors to assess investment opportunities, the OIIPRS could serve as one of
the parameters.
In India, a significant number of surveyed large and medium FinTechs have well-
established IP management procedures to protect IP that originates from OI. Few of the
Indian FinTech start-ups seem to have IP management strategies in place as well. While
this study has focused on FinTechs in India, the model that is proposed in this article can
apply to software firms worldwide. The risk factors and corresponding weights computed
with AHP will apply as-is for software firms worldwide. However, additional research is
required to study the applicability of the IP risk factors that are identified for the software
industry to non-software industries.
Sustainability 2023,15, 11036 15 of 19
The current research scope is limited to considering factors that are configurable by
firms to attain lower levels of IP risk while engaging in OI. The influence of the eight
identified non-configurable factors on the OIIPRS needs further analysis. Both configurable
and non-configurable factors can be included in the AHP model to perform pairwise
comparison to compute the weights of each factor. Thus, an enhanced version of the
open innovation intellectual property risk assessment model with both configurable and
non-configurable factors can be developed in future.
As the software industry is fast evolving and product life cycles are becoming shorter,
the factors and weights used in the model need reassessment on a yearly basis. Firms
engaging in OI are also recommended to assess the IP risk on a monthly basis to formulate
appropriate mechanisms to lower IP risk. The available literature on OI is limited to
assessing firms’ performance. There is no research around measuring IP risk involved in
OI. Thus, comparison of the scores generated by the proposed model in this research with
another model is not viable. When researchers develop other IP risk assessment models
for OI, a comparison of results produced by such models and the proposed model in this
research can be performed to assess the robustness of the model.
Further research is required to assess how the identified IP risk factors can be con-
figured to devise contextual IP management policies in order to reduce IP risk levels and
move up the risk maturity continuum for the various company segments such as micro,
small, medium, and large organisations, and start-ups. The impact of the involvement of
other parties such as universities and individuals, and the use of open-source software in
OI can also be investigated in further research.
Author Contributions:
Conceptualisation, B.S.A., D.B. and R.S.K.; methodology, B.S.A., D.B. and
R.S.K.; software, B.S.A.; validation, formal analysis, investigation, resources, and data curation, B.S.A.;
writing—original draft preparation, B.S.A.; writing—review and editing, D.B.; visualisation, D.B.;
supervision, D.B.; project administration, B.S.A. All authors have read and agreed to the published
version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Conflicts of Interest:
The authors declare that they have no known competing financial interests or
personal relationships that could have appeared to influence the work reported in this paper.
Abbreviations
The following abbreviations are used in this manuscript:
AHP Analytic hierarchy process
Cr Crore, equivalent to 10 million
CAGR Compound annual growth rate
IBM International Business Machines
IP Intellectual property
MCDM Multi-criteria decision-making
OI Open innovation
OIIPRS Open innovation intellectual property risk score
OIIPRMM Open innovation intellectual property risk management model
Rs Indian Rupees
USD United States Dollar
Sustainability 2023,15, 11036 16 of 19
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