=Paper=
{{Paper
|id=Vol-2927/paper3
|storemode=property
|title=Risk Assessment of Innovative Projects: Development of Forecasting Models
|pdfUrl=https://ceur-ws.org/Vol-2927/paper3.pdf
|volume=Vol-2927
|authors=Volodymyr Gorokhovatskyi,Olena Sergienko,Igor Sosnov,Maryna Tatar,Evgeniy Shapran
}}
==Risk Assessment of Innovative Projects: Development of Forecasting Models==
https://ceur-ws.org/Vol-2927/paper3.pdf
18
Risk assessment of innovative projects: development of
forecasting models
Volodymyr Gorokhovatskyi1 [0000-0002-7839-6223],
Olena Sergienko2 [0000-0002-9796-9218], Igor Sosnov2 [0000-0003-0027-5488],
Maryna Tatar3 [0000-0002-1111-7103], Evgeniy Shapran2 [0000-0002-9236-0905]
1
Kharkiv National University of Radio Electronics, Ukraine
2
National Technical University «Kharkiv Polytechnic Institute», Ukraine
3
National Aerospase University «Kharkiv Aviation Institutе», Ukraine
volodymyr.horokhovatskyi@nure.ua, serhelenka@gmail.com,
igor.i.sosnov@gmail.com,
marina.sergeevna.tatar@gmail.com, evgen.shapran1948@gmail.com
Abstract.
The purpose of this article is development a systematic dynamic complex model of genera-
tion and risk assessment of innovative project, on the bases of which a scenario modeling of
many risks influence arising at certain stages of project implementation in the target area.
For article purpose realization, the paper proposes a complex toolkit for modeling the inno-
vative projects risks in the direction of their impact on performance indicators in scenarios,
which involves the implementation of the following stages of modeling: Stage 1. Collection
and processing of project data; Stage 2. Evaluation of innovation project efficiency indicators;
Stage 3. Formation and assessment of many risks of innovation project by components, nature
and impact strength; Stage 4. Modeling of innovative project development scenarios.
The implemented set of models makes possible to compare all components of efficiency and
riskiness, which determine the integrated aggregate level of project risk by components of life
cycle risks, target project risks and scenarios depending on environmental factors and managers
propensity to take risks, and solves the problem of positioning the real indicators state of inno-
vation project efficiency in a comparative dynamic context based on three-level assessment,
due to structural elements of risks and identification of possible and promising deadlines and
time horizons by stages of the project life cycle, critical paths and reserves which allow us to
achieve the main goal of improving the innovative projects implementation efficiency.
Keywords: innovative project, life cycle, risks, simulation model, business entities, chal-
lenges, scenario modeling, efficiency criterion.
I Introduction
Today realities show that modern world faces a large number of global challenges
such as geopolitical, social, economic, biological, demographic, climatic, technologi-
cal, informational, cultural, which are described by Tatar (2020). Global challenges
Copyright © 2021 for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0).
19
radically change the socio-economic relations and interaction between states and
business entities within states, require concentration and pooling of opportunities at
all levels of government, determine the need to adjust the national strategy of socio-
economic development and its innovative reorientation, encourage to fundamentally
new approaches formation for business entities innovation activities management.
In the context of global challenges, the economic entities innovative activity is
characterized by an increased risk level. The research of Ukrainian industrial enter-
prises innovative activity state shows that its level remains quite low. The share of
industrial enterprises that have implemented innovations is about 11%. According to
the Innovation Development Index presented by Bloomberg in 2018, Ukraine ranks
53rd among the 60 surveyed countries. The results of research by Ukraine State Sta-
tistics Service show that one of the main reasons that constrain the business entities
innovation activity is the imperfection of institutions, especially the political, regula-
tory and business environment; high risks in the innovative projects implementation.
In this regard, the project risks analysis, assessment and management is relevant be-
cause it will give an opportunity to really assess the prospects, in terms of selected
project risk.
The innovative project risk is the possibility that the company will incur losses or
in the form of additional costs in excess of the forecast; or due to exceeding the
planned time of implementation of the innovation project stages; or due to loss of
time due to the risk associated with the innovation commercialization in the market;
or will receive income below those expected. These types of resources loss lead to a
possible loss of profit under innovative project implementation in comparison with
the forecasted variant. To ensure the objectivity of the analysis of enterprise innova-
tion activities effectiveness it is necessary to quantify the innovative project risks
value.
Problems of innovative projects research, their development in the conditions of
risks are revealed in papers of such scientists as A. A. Abdalah, T. Barton, V.V. Bu-
gas, I.V. Stepanova, A.V. Skrypka, W. Schenkeri and P. Walker, G.I. Karlova, V.O.
Vasylenko, N.N. Lepa, R.N. Lepa, A.V. Grinyov, V.M. Grinyova, S.S. Sviridova and
N.M. Gazheva, O.M. Zborovska, О.О. Okhrimenko and N. E. Skorobogatova and
others.
The necessity and relevance of innovative projects research in condition of risks
and today's global challenges, combined with the processes of integration, simultane-
ous neo-industrialization and deindustrialization are confirmed by the papers of for-
eign authors Barton, Schenkeri and Walker (2003) which emphasize the beginning of
the process of forming the latest stage of society development – "risk society" – and
claim that humanity has already entered this new phase / stage of development. This
is due to the fact that in modern conditions most of the threats and risks caused by
them are no longer local in nature, but become global. The main problem of future
economic growth will be not so much the growing need for funds to finance new in-
vestments, but the need to reserve capital to meet those needs that will be caused by
risks.
Researchers Lityuga and Revutska (2012) in the paper "Risks of innovation activi-
ty and modern outsourcing models of its implementation" to the innovation process
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risks types include: 1) the risk of wrong choice of innovation project; 2) the risk of
not providing the innovative project with a sufficient funding level; 3) marketing
risks; 4) risks of non-fulfillment of economic agreements (contracts); 5) the risk of
increased competition; 6) the risk of staffing insufficient; 7) risks associated with
securing property rights to the innovative project.
Grigorieva (2008) in her paper "Problems of risks that arise during the implemen-
tation of innovative projects and methods of their quantitative measurement" analyzes
the risk concept, considers options for innovative risks and provides different classifi-
cations of risks that may face the company during implementation of innovative pro-
jects.
Risk assessment of investment in innovation are considered in Kushnir and Ver-
nydub (2018) papers. The paper of Bugas, Stepanova and Skrypka (2019) is devoted
to the international experience of risk management of enterprise innovative activity.
Iarmosh, Prokhorova, Shcherbyna, Kashaba and Slastianykova (2021) investigate
innovativeness of the creative economy as a component of the Ukrainian and the
world sustainable development strategy.
For successfully building of innovative projects mathematical model, it is neces-
sary to have a well-established theoretical basis and significant empirical experience.
Such model should be representative; take into account the key factors influence; take
into account the impact of major constraints; be flexible and predictable. In essence,
these requirements are common in the construction of any mathematical model. Such
requirements are met by traditional stationary statistical models. Innovative behavior
in such models is interpreted as a one-time action performed by the innovator (busi-
ness entity). The consequences of such action should be Pareto-optimal and lead to
equilibrium in the innovation market. However, considering the objective complexity
of innovation processes in general and innovation projects in particular, another spe-
cific requirement must be put forward for modeling such processes - taking into ac-
count a high degree of uncertainty and risk. However, most methods and models do
not take into account the risks impact.
Methods of innovative projects risk assessment include the method of project sen-
sitivity analysis, the method of scenarios and methods of simulation. These tools are
used in the paper to assess the risk and effectiveness of innovative projects. Among
the methods of risk management, scientists identify the following methods: risk allo-
cation; diversification; reduction of uncertainty; limitation; hedging; insurance.
When evaluating the innovative projects effectiveness, the resulting indicator is
usually one of the efficiency criteria: net present value (NPV), internal rate of return
(IRR), profitability index (PI) and payback period.
The most common of these are the expected net present value method, sensitivity
analysis and the risk-adjusted discount rate method. The general advantage of these methods
is their relative simplicity and clarity. Therefore, these methods are quite common in
practice. But there is a common disadvantage for all these methods – they do not directly
measure the risk. There is another difficulty in their application – due to the uniqueness of
each innovation, there are no commonly used methods of objective assessment of the
innovative project effectiveness. So the problem of objective assessment of the inno-
vative project effectiveness and risks level remains relevant. Based on the chara-
?teristics of the most important innovation project features, it is necessary to assess its
21
riskiness and innovative attractiveness. The usage of traditional methods of investment
projects efficiency evaluation does not provide a sufficiently sound and reliable answer,
methods of taking into account the risk of innovative projects have significant shortcomings
and need to be improved. Economic and mathematical methods that can be used to select
effective innovation projects include the use of expert assessments, simulation, scenario
method, fuzzy set apparatus, methods for solving multicriteria problems and others.
The analysis of methods and models and their shortcomings which are used for
innovative projects and risks modeling is carried out (Tab. 1).
Table 1. Analysis of methods which are used for innovative projects and risks modeling
Local tasks in innovation Existing methods and models for Disadvantages of the methods
and risks research solving the problem
matrix methods of strategy formation, usage of individual methods is ineffective,
methods of analogies, expert methods; it is desirable to use combinations of differ-
active search methods (surveys, exhibi- ent methods to obtain more accurate result
Innovative projects tions, fairs, publications); brainstorm-
purposes, tasks deter- ing, Delphi method, passive search
?ination methods (patent analysis, marketing
research, proposals of consumers,
developers and inventors);
SWOT-analysis, system approach
methods of multidimensional statistical the usage of individual methods does not
analysis (cluster analysis, factor analy- give a complete objective assessment of the
Assessment of innovation
sis, taxonomy methods, etc.), expert potential and results, more desirable is
potential and results of
methods; combination of different methods; limited
enterprise innovation
integrated indicators; sets of indicators for evaluating the results
activity
correlation-regression analysis and of innovation activity
optimization methods
standard methods for evaluating the impossible to assess sufficiently complete
effectiveness of investment projects; assessment of the potential risks associated
projects break-even analysis with the implementation of innovations and
the impact of many factors, information on
which is unclear or absent.
methods of sensitivity analysis of takes into account the change of one factor
projects influencing the project results at constant
levels of other factors, which is not true
analysis of project development require a large number of operations for the
Evaluation of innovative scenarios selection and analytical processing of
projects effectiveness information for scenarios, a limited number
of scenarios; a high proportion of subjectiv-
ity in the scenarios formation
decision tree technical complexity of the method for
large tree sizes, high subjectivism in
determining probability estimates
simulation methods (Monte Carlo) high sensitivity of the result to the laws of
probability distribution of input variables;
the accuracy of the results depends on the
initial assumptions and taking into account
the interaction of the input variables
statistical methods, methods of require a large number of observations to
economic analysis, method of obtain a qualitative forecast, the inability to
Evaluation of the
analogies, analysis of time series, take into account the individual characteris-
innovation effectiveness
methods of correlation and regression tics of the research objects development
analysis, methods of expert evaluations
22
model of susceptibility of enterprises to the model is based on expert judgment, i.e.
innovation based on the method of inaccurate and subjective
analysis of hierarchies
Estimation of the effect of model of diffusion of new products the process of increasing consumers of new
enterprises innovation taking into account uncertainty products is modeled
activity technology diffusion model the process of replacing existing technolo-
gy with more modern, new technology is
modeled, but the spread of innovations
between enterprises is ignored
methods for evaluating the innovative the proposed management methods are
projects effectiveness, methods of reduced to the selection of effective
regression analysis, expert methods, innovation projects
SWOT-analysis, simulation, methods
Innovative projects of dynamic programming for the
management allocation of resources between innova-
tive projects
systems analysis methods to identify models are generally conceptual in nature
the elements of the control system and
the interrelation between them
To ensure the objectivity of the analysis of enterprise innovation activities effec-
tiveness it is necessary to quantify the innovative project risks value. There are many
approaches to risk assessment of innovative projects. However, due to the uniqueness
of each innovation, there are no commonly used methods of objective assessment of
the innovative project effectiveness. That’s why the problem of objective assessment
of the innovative project effectiveness and risks level remains relevant.
So despite significant developments in this area, insufficiently researched, in our
opinion, remain some aspects of the application of modern economic and mathemati-
cal modeling to assess the future risks of innovative projects, which is especially rele-
vant in today's global challenges.
II Methodology and Data
The research is based on the confirmation of the following empirical hypotheses:
Hypothesis 1 – the research of enterprise innovative activity efficiency is defined
by necessity of reliable quantitative estimation of innovative projects local and aggre-
gate risks level, and also influence strength.
Hypothesis 2 – the presence of certain specific features of innovative projects,
which are determined by the high degree of uncertainty and risk associated with the
project life cycle phases and its target orientation.
Hypothesis 3 – each phase (stage) of the innovative project life cycle has its own
characteristics that take into account different types of risks, which differ in content
and main causes.
Hypothesis 4 – each innovation project can be characterized by efficiency indica-
tors in terms of costs, revenues and deadlines, which form a set of target risks of the
innovation project (risk of overspending, risks of underfunding, risks of overspending
time on project stages realization).
Investigating the innovation processes effectiveness and considering the planning,
development, implementation, and management of innovative projects, first of all, the
condition of system management of dynamic object under the influence of external
23
and internal factors is necessary. In view of this, the article purpose is development a
systematic dynamic complex model of generation and assessment of innovative pro-
ject risks on the bases of which a scenario modeling of the impact of many risks aris-
ing at certain stages of project implementation in the target area.
For achievement the purpose, the paper proposes a complex toolkit for modeling the in-
novative projects risks in the direction of their impact on performance indicators for scenari-
os, which involves the implementation of the following stages of modeling:
Stage 1. Collection and processing of initial project data.
Stage 2. Evaluation of the innovation project efficiency indicators.
Stage 3. Formation and assessment of many innovation project risks by components, na-
ture and strength of impact.
Stage 4. Modeling of scenarios of innovative project development.
The methods of assessment the project investment attractiveness were used for
complex algorithmic model implementation, at the same time the innovative project
indicators calculation was carried out in the dynamics of 7 years, as well as scenario
simulation with multicriteria selection and implementation of alternatives using full-
featured software Vensim PLE, which occupies an important place among various
forecasting methods of management decisions results as a basis for forecasting and
analysis of high complexity systems.
The choice of simulation methodology for research of innovation projects risks
and construction of forecast models is defined by the following advantages that are
realized in paper:
– simulation modeling is a series of numerical experiments designed to obtain
empirical estimates of the degree of influence of various factors (initial values) on
some dependent results (indicators);
– the ability to establish interrelations between the initial and output indicators in
the form of a mathematical equation or inequality;
– setting the laws of probability distribution for the key model parameters;
– conducting computer simulations of the values of key model parameters;
– calculation of the main characteristics of the distributions of initial and output
indicators;
– wide possibilities of use, especially in the conditions of uncertainty and risk;
– convenience in combination with other economic and statistical methods.
The scenario method makes possible to combine the research of the resulting
indicator sensitivity with the analysis of probabilistic estimates of its deviations. In
the general case, the procedure for using this method in the process of investment risk
analysis includes the following implementation:
1. Identification of several options for changes in key initial indicators (eg,
pessimistic, most probable and optimistic).
2. Each variant of change a corresponding probabilistic estimate is assigned.
3. For each option the probable value of the criterion is calculated as well as
estimate of its deviations from the average value.
4. The analysis of probability distributions of the received results is carried out.
5. The method makes possible to obtain a sufficiently clear picture for different
options for project implementation, as well as provides information about the
24
sensitivity and possible deviations.
6. The usage of software can significantly increase the efficiency of the analysis
by virtually unlimited increase in the number of scenarios and the additional variables
introduction.
The research information base for the practical implementation of innovative pro-
ject complex algorithmic model is the initial data of the industrial enterprise on the
example of the project of new equipment creation for plastic processing, i.e. advanced
model of thermoplastic machine, and new production organization – the department
for the production of plastic products by injection molding on the basis of new auto-
matic thermoplastic machines.
III Results and analysis
The main difference between an innovative project (IP) and an investment project
is the high degree of uncertainty and risk associated with the phases of the project life
cycle. An innovative project as an object of evaluation has the following main fea-
tures: sign of change; sign of a limited ultimate goal; sign of limited duration; sign of
limited budget; sign of limited necessary resources; sign of novelty for the enterprise
implementing the project and for the market of the expected demand for the product
(service) created in the project; sign of legal and organizational support; sign of dif-
ferentiation from other enterprise projects.
Each phase (stage) of the innovative project life cycle has its own characteristics
that take into account the types of risks (Tab. 2). The main conditions that negatively
affect the project effectiveness are:
– shift of the planned terms of the end of this or that phase (12 stages);
– increase in planned costs associated with overspending of innovation funds (12
stages);
– reduction of planned revenues associated with additional risks that restrain the
innovation commercialization in the market (only in the last 4 stages).
Table 2. The results of classification of the main causes of the innovative project
life cycle risks
Stage contents Causes of risks at the innovative project life cycle stages
1. Marketing and Probability of negative results of marketing and research works; the probability
research of market of erroneous discovery of a new idea or technology; the probability of occurrence
needs (identification of new problems during new ideas formation that can not be solved at the current
of ideas from level of science and technology; risk of erroneous segmentation of the innovation
consumers) market; the risk of erroneous choice of the target market segment of the strategy;
the risk of erroneous of innovation goals formation
2. Generation of ideas Other sources of ideas for creating new products do not meet the needs of
from other sources consumers
3. Selection of Risk of erroneous selection of ideas and non-selection of business ideas; risk with
business ideas the probability of new product success: technical completion of development,
launch into commercial production subject to technical completion, economic
success subject to launch into commercial production
4. Development of the Inefficiently developed product concept; lack of the principle of design by order
product concept and of consumers; the risk of erroneous development of the initial positioning of the
its verification product and brand; ineffective testing of the concept on the relevant group of
target consumers in order to find out their reaction
25
5. Business analysis The risk of erroneous description of the volume of the structure of the target
(analysis of market and consumers on it, the proposed product positioning, as well as market
production and sales share and the planned enterprise share;
opportunities) incorrect information about the planned goods price, ab distribution out the
principles; the risk of erroneous total sales forecasting; risk of erroneous costs
and profits forecasting
6. Product Ineffective transition of the idea into a real product (incorrectly developed R&D
development strategy); the risk of not finding unique resources due to the technical features of
the innovation project; risk of interaction with partners (contractors); the cost of
product development was higher than estimated
7. Tests in market Ineffective testing of a new product in market trials; incorrect reaction of dealers
conditions (trial to the appearance of a new product, its use and sale; erroneously determined
marketing) market size and overall sales forecast
8. Preparation and It is inefficient to start design, technological and organizational preparation of
production of goods production for the purpose of goods introduction in the market; risks associated
with securing property rights under the project; the probability of occurrence of
incidental problems when using innovations that cannot be solved at the current
level of science and technology
9. Implementation Ineffective methods of informing potential consumers about a new, not yet
known product, persuading them to try this product and ensure sales through
retailers; the new product was poorly positioned, its advertising campaign was
ineffective or the price was set too high; the risk of erroneous development of
pricing and promotion strategy; the risk of unsuccessful organization of the sales
network and the system of goods promotion to the consumer; the product has
design defects; social, environmental and state restrictions; global risks and
challenges
10. Growth The idea itself was good, but the market size was overestimated; the corre-
?ponding shock of competitors was stronger than expected; ineffectively
developed strategy of differentiation
11. Maturity Reduction of the product life cycle; the risk is associated with failure to achieve
the goal of marketing "profit maximization and market share protection"; ineffi-
ciently developed strategy for diversification of brands and models
12. Decline The risk is associated with failure to achieve the goal of marketing "reducing
costs and maintaining sales"
To ensure the objectivity of the analysis of enterprise innovation activities
effectiveness in terms of risk, it is necessary to use adequate tools of methods and
models for assessing and forecasting the whole set of innovation project risks.
Let's consider the offered model of an estimation of aggregate risks of the
innovative project in more detail on the basic stages and steps which are realized in
paper.
Stage 1. Collection and processing of initial project data. This stage involves
the formation of a database of statistical factors, result indicators and a complete list
of risks to build models of risk management and their impact on the resulting
variables.
In paper one of the most important assessments of the effectiveness of the i - th
innovative project is its revenue eit . Revenue from the innovative project implemen-
tation is forecasted by the company before deciding on its implementation, so it is
very important that such forecast was as accurate as possible.
Based on the project business plan, each innovative project can be characterized by cost
indicators ( cti ), where 1, T is the stage of the innovative project life cycle, and revenue
26
indicators ( eti ), cash flows during the project start from the stage of innovation implementa-
tion, i.e. t 9, T , where T 12 according to the innovative project life cycle stages
classification.
It should be noted that the initial data for assessing the innovative projects effectiveness
are the forecast values of their cash flows:
– the flow of discounted costs for the project dcti (cti , t , r )
– the flow of discounted revenue of the project deti (eti , t , r ) , where r discount rate.
For building a complex model and its components the following software variables that
characterize the production and business processes are used: Cost risk; Income risk; Final
performance of thermoplastic automatic machine (TAM); Average price; Number of
manufactured products; Operating costs; Running costs; Sales volume; Equipment
costs; Income tax rate; Income tax; Taxable profit; Investments; Net profit; Net cash
flow; Service life; The number of operating equipment; One-off costs; Unit value;
Book value; Depreciation of production equipment; Depreciation of production
building; Quantity of installed equipment; Quantity of operating equipment; NA
equipment per year; Wear; Wear of press forms; Accounts payable; Unit debt; Rede-
velopment costs; Establishment and maintenance costs; Quantity of equipment units;
Profitability Index; Average discount income; Payback period; NPV; Discount costs;
Discount income; Discount rate; Amount of discount income; Amount of discount
costs.
Stage 2. The innovative project efficiency indicators assessment. The next step
in assessing the innovative project effectiveness is such indicators calculation as:
– net present value of the project NPV i (deti , dcti ) ;
– profitability index of the project IP i (deti , dcti ) ;
payback period of the project IT i (deti , dcti , T ) .
Stage 3. Formation and assessment of many risks of an innovation project by
components, nature and strength of impact.
In the process of selecting a priority innovation project and / or multidimensional ranking
of alternatives by efficiency indicators in terms of risks under certain scenarios, it is
important to prepare the project business plan and assess its overall integrated efficiency, as
well as the distance from the moment of project implementation. The longer this period, the
greater the degree of uncertainty of the impact on project indicators of both external and
internal factors. Therefore, the project effectiveness assessment should be supplemented by
an assessment of the risks that arise at each stage of the project life cycle (Table 2) and reflect
the most significant risks of each of the life cycle stages (R1 – R12) and the overall innovative
project risk assessment as a whole.
The next group of risks studied in the model is the target risks of the innovation project
(Tab. 3), which can occur at any stage of the life cycle with certain features, namely:
– risks of overspending ( vcti );
– risks of underfunding ( veti );
– risks of overspending time on project stages realization ( vtti ).
27
For algorithm implementation, it is necessary to conduct an in-depth analysis of model
variables to identify risk sources.
Table 3. Target risk analysis of the innovative project
Risk Description
It can occur at any stage of the project life cycle. According to the studied project,
the costs are carried out to a greater extent during the first year, because during
this time all 8 first stages of the life cycle are completed. Therefore, we will
Risk of overspending assume that the impact of risk must be taken into account when modeling the cost
i of equipment unit and the cost of installation and adjustment of equipment opera-
( vct )
tion. These types of costs are present to the 12th period of the life cycle, as it is
planned to introduce the equipment gradually. It is also worth considering the
risks of exceeding the current cost on 1 hryvnia of sold products, as the company
can plan or forecast these costs, but exactly in the future it is impossible to know.
It can occur due to a decrease in expected sales. So the impact of this risk type
Risk of underfunding
should be taken into account when calculating the variable "Sales volume". Risks
i
( vet ) of loss of income loss appear at the 9th stage of the life cycle, at the stage of
implementation, and continue until the end of the period.
It is advisable to study within the first eight stages of the life cycle, as the most
Risk of overspending time on important in this regard are the stages of preparation for the new products produc-
project stages realization tion, the timing of which may deviate significantly from the planned. Since under
i
( vtt ) the terms of the project all 8 stages are implemented in the first year, so this
excludes the possibility of a detailed study of time spending during this period.
Let us make a basic assumption about the method of formalizing the reflection of the risk
impact at each stage of the life cyrcle on the amount of expected costs (investment, income,
time) which is proportional to the risk amount of the respective stage. The rationale for the
efficiency of the basic assumption is the innovation project uniqueness, which does not make
possible to estimate in advance the law of distribution of the random value of risk in a single
implementation scenario. The paper seems to be rational to obtain an optimistic, most
probable and pessimistic limits of risk assessment.
The meaning of the innovative project risk indicators, which will be reflected in the
simulation model is presented in the form of the following criteria and restrictions:
1) K1 – a criterion that characterizes the total amount of overspending of investments in
the implementation of all stages of the innovation project, which must be minimized under
certain other conditions;
2) K2 – criterion that characterizes the condition of minimizing the total amount of excess
of the planned time of implementation of the first eight stages of the innovation project,
related to the first two phases (innovation development and innovation implementation);
3) K3 – criterion that takes into account the life cycle of innovation and reflects the time
minimization due to the risk associated with the innovation commercialization in the market;
4) K4 – criterion that characterizes the total amount of loss of projected income
associated with market risk (total loss of income), which must be minimized under certain
other conditions;
5) O1 – restriction, which is a formalization of the requirement not to exceed the
investments overspending at each stage of the planned amount of total investment, aimed at
possible risks compensating;
6) O2 - restriction, which is the implementation of the requirements for the allowable
time limit of the innovative project on two components: the total duration of deviations of the
first eight stages of the innovation project, starting with marketing and research and ending
with the stage of preparation and development of innovation should be in acceptable
28
established time frames; the next component is the presence of the risk of extension of the
terms of innovative project commercialization associated with the commercialization of
innovations in the market;
7) O3 - restriction that reflects the total loss of income due to the impact of market risks.
i
For the integrated aggregate risk assessment of the innovation project ( V ), it is
proposed to use the apparatus of fuzzy sets. The calculation of the integrated assessment
involves the implementation of the following steps:
Step 1. Classification of risks by determining the linguistic variable and fuzzy class-
?fication of values of indicators of each type of risk. For the variable that characterizes the
risk of overspending, we define the linguistic variable "Risk level vcti " with the introduc -
ion of five fuzzy subsets R of the set of values vc :
i
t
R1 – fuzzy subset – "very low risk",
R2 – "low risk",
R3 – "average",
R4 – "high risk",
R5 – "very high risk".
Similarly, we define fuzzy subsets for the risks of loss of income and overspending.
As an integrated innovative project risk assessment it is proposed to introduce the lin-
guistic variable "Innovation Project Risk" with the values {Very low project risk, Low pro-
ject risk, Medium project risk, High project risk, Very high project risk}.
Step 2. Construction of membership functions of fuzzy sets. On the bases of the
analysis of the values of the linguistic variable "Risk of the innovation project", the member-
ship functions are determined , which correspond to fuzzy T-numbers r. Subsets
R are formed by constructing membership functions. Since the upper and lower values
are set for each risk type, it will be advisable to use trapezoidal membership functions.
Step 3. Assess the significance of innovative projects partial risks for integrated risk as-
sessment. Each type of risk at each stage of the life cycle is associated with an assessment
p of the significance of this stage and an assessment p of the risk significance to assess
t v
the project overall risk.
Step 4. Construction of comlex innovative project risk assessment. The integrated risk in-
dicator of innovative project is calculated by the formula:
V i pvt vj j ,
5
t ,v j 1
where j is the value of risk depending on the propensity of the decision maker;
p p p is assessment of the total risk of the project stage.
vt t v
29
Stage 4. Modeling of innovative project development scenarios.
Thus, according to the results of the previous stages of evaluation, each scenario of inno-
vation project development is characterized by the following set of evaluation criteria of
innovative project:
Q i NPV i , IP i , IT i ,V i , i 1, n .
Therefore, the problem of ranking scenarios from a set of alternatives becomes a
problem of multi-criteria selection. This step should take into account the determination of
the criteria weights, because they show the degree of risk appetite and individual preferences
of managers, so they can be subjective. According to the obtained values of the generalizing
criterion, the best scenario of the situation development is determined.
For the practical implementation of the proposed methods of innovation project
risk management the simulation model of an appropriate innovative project is built on
the example of new equipment creation for plastic processing, i.e. advanced model of
thermoplastic machine, and new production organization – department for the produc-
tion of plastic products by injection molding on the basis of new automatic thermo-
plastic machines. The implementation of the project will diversify the company's
activities and increase company's sales. The initial data on the project are given in
Tab. 4-5.
Table 4. Calculation of the innovative project indicators
№ Indicators name Years
1 2 3 4 5 6 7
1 Number of operating
20 56 95 95 95 75 39
equipment
2 Number of plastic products
per year, thousands of 2200 6160 10450 10450 10450 8250 4290
pieces
3 Sales volume, thousand
79,2 221,76 376,2 376,2 376,2 297 154,44
euros
4 Current expenses, thousand
49,1 137,49 195,62 195,62 195,62 163,35 84,94
euros
5 Depreciation of production
9 25,2 42,75 42,75 72,75 33,75 17,55
equipment, thousand euros
6 Wear of special purpose
1,8 5,04 8,55 8,55 8,55 6,75 3,51
devices, thousand euros
7 Depreciation of a
production building, 0,8 0,8 0,8 0,8 0,8 0,8 0,8
thousand euros
8 Taxable profit, thousand
18,5 53,23 128,48 128,48 128,48 92,35 47,64
euros
9 Net profit, thousand euros 12,95 37,26 89,94 89,94 89,94 64,65 33,34
10 Net cash flow, thousand
24,55 68,3 142,04 142,04 142,04 105,95 55,2
euros
In paper Abdalah A.A. (2004) the main causes of the innovative project risks in accord-
ance with the stages of the life cycle are identified, and expert assessments of the lower and
upper limits of each type of risk are determined respectively (Tab. 6).
30
Table 5. Calculation of investments
№ Indicators name Years
1 2 3 4
1 Costs for creation and operation of a prototype of the improved
8,0
model of thermoplastic automatic machine, thousand euros
2 Capital costs for partial reconstruction of thermoplastic
142,5
automatic machine, thousand euros
3 Expenditures on re-planning of the old case and carrying out
repair and construction works in production of products from 20,0
plastic, thousand euros
4 Costs for equipment for plastic products production, thousand
45 81 87,75
euros
Total 170,5 45 81 87,75
Table 6. Expert assessments of risks that arise at each innovation project life cycle stage
Stage contents Risks of overspending Risks of underfunding Risks of overspending
time on project stages
vc vc vc
i
t
i
t
i
t ve ve ve
i
t
i
t
i
t realization
vtti vtti vtti
vcti vcti veti veti vtti vtti
1. Marketing and
research of market
needs (identification 0,01 0,02 – – 0,05 0,07
of ideas from
consumers)
2. Generating ideas
0,05 0,06 – – 0,04 0,05
from other sources
3. Selection of
0,0025 0,003 – – 0,05 0,06
business ideas
4. Development of
0,005
goods concept and its 0,006 – – 0,02 0,05
check
5. Business analysis
(analysis of
0,005 0,006 – – 0,05 0,06
production and sales
opportunities)
6. Product
0,01 0,02 – – 0,06 0,07
development
7. Tests in market
conditions (trial 0,005 0,006 – – 0,05 0,06
marketing)
8. Preparation and
0,02 0,03 – – 0,06 0,07
production of goods
9. Implementation 0,03 0,04 0,05 0,06 0,04 0,05
10. Growth 0,04 0,05 0,04 0,05 0,03 0,07
11. Maturity 0,02 0,03 0,05 0,06 0,06 0,07
12. Decline 0,01 0,02 0,02 0,03 – –
The results of the calculation of a complex innovative project risk assessment using
fuzzy sets are shown in Fig. 1.
31
. Risk assessment of the 1st stage of the innovative project life cycle
Risk assessment of the 12th stage of the innovative project life cycle
Aggregate risk assessment of an innovative project
Fig. 1. The results of the calculation of a complex innovative project risk assessment
using fuzzy sets
Taking into account the identified risks, the built simulation model has the form which is
shown in Fig. 2.
32
Service life cost risk - 1-8
final perf of TAM cost risk - 9
Number of Number of operation cost risk - 10
equipment Number of operation COST RISK
manufactured products equipment (t-5) cost risk - 11
Average Price