Optimal Method Selection for Assessing the Prospects and Readiness

for Market Commercialization of Scientific Researches and

Development

Mitus Kseniia

, Baranov Alexey

and Drebot Alexander

Institute of Finance, Economics and Management, Sevastopol State University, University street 33, Sevastopol, Russia

Keywords: Commercialization, Research, Scientific Development, Assessment Methods, Criteria, Commercial Potential.

Abstract: The article is devoted to the issues of justifying the method selection for the prospects and readiness assessing

for market commercialization of the results of research activities of universities. A review of modern methods

for assessing the commercial potential of the intellectual activity results with the identification of their

strengths and weaknesses is carried out. The criteria selection for assessing the prospects of using various

methods to assess the prospects and readiness for market commercialization of scientific research and

development taking into account the practicality of using the methods is substantiated. Based on Kemeny's

median method, these methods were ranged, which made it possible to determine the most optimal method

for assessing the prospects and readiness for market commercialization of research and development, as well

as assessing their commercial potential, which is the TPRL methodology.

1 INTRODUCTION

The current stage of economic development in the

world is characterized by active development and

implementation of innovations in production. An

integral and important part of any innovation is the

process of commercializing the results of intellectual

activity (Azatbek et al, 2019; Ablaev, 2018). This

process allows you to distribute the results of research

(project) to a wide range of customers, to investigate

the effectiveness of the implementation of these

results, to provide the necessary income for

researchers for the further circulation of intellectual

processes (Zharinova, 2011). Despite the importance

of commercializing the results of intellectual

property, this issue is not fully understood. So there is

no unified approach to the applied terminology and

methods of assessing the commercial potential of

sciential and scientific and technical results. The

latter, as practice reveals, leads researchers to

erroneous results.

In this connection, the economic and

mathematical justification of sciential and scientific

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and technical results selected from a variety of

methods for assessing the commercial potential of

scientific and technical results is one of the most

important and urgent scientific issues, the solution of

which will allow at the early stages of design

(development) to select the most promising areas of

research and discard deliberately unrealizable and

unpromising developments.

2 THE PURPOSE AND

OBJECTIVES OF THE STUDY

The aforementioned gives grounds to formulate the

purpose of this work, which incorporates the

economic and mathematical substantiation of the

selection of the most adequate method for assessing

the readiness for market commercialization of

research and development.

To achieve this goal, the following tasks were set

and solved:

- a review of widely used methods for assessing

the commercial potential of research and

320

Kseniia, M., Alexey, B. and Alexander, D.

Optimal Method Selection for Assessing the Prospects and Readiness for Market Commercialization of Scientiﬁc Researches and Development.

DOI: 10.5220/0010667900003223

In Proceedings of the 1st International Scientiﬁc Forum on Sustainable Development of Socio-economic Systems (WFSDS 2021), pages 320-327

ISBN: 978-989-758-597-5

development, as well as their readiness for market

commercialization, was carried out;

- selection and justification of criteria for ranging

methods for assessing readiness for market

commercialization of research and development;

- using the Kemeny median method to range the

methods for assessing the readiness for the market

commercialization of research and development and

to justify the selection of the most optimal method.

3 METHODOLOGICAL STUDY

The methodological basis of this study is the

provisions of classical economic theory, theory of

innovation, theory and practice of project

management, as well as fundamental and applied

developments of foreign and domestic scientists in

specified areas.

The dialectical method predetermining the study

of phenomena in development and interrelation is

used. The methods of systemic, logical and economic

analysis, as well as methods and techniques of

multivariate analysis using expert assessments are

applied in the study. The Kemeny median method as

a mathematical model that allows ranging the

methods for assessing commercial readiness and the

implementation of scientific developments was

employed.

4 RESEARCH RESULTS

Commercialization of sciential and (or) scientific and

technical results is the activity to involve sciential and

(or) scientific and technical results in the economic

circulation (Federal Law No. 127-FZ, 1996). Part 4 of

Art. 16.4 of the Federal Law "On Science and State

Scientific and Technical Policy" (Federal Law No.

127-FZ, 1996) with state support for innovative

activities of universities provides a procedure for

determining the permissible level of risks including

financial, and basic criteria for managing them. An

important place in this process is taken by the

assessment of the prospects for the commercialization

of innovation and (or) sciential and (or) scientific and

technical products of an innovative project.

It should be noted that at present, a sufficient

number of methods have been developed for

assessing the prospects and readiness for market

commercialization of scientific research and

development. They differ in levels of complexity,

reliability, conditions of use, which actualizes the

problem of choosing those of them that would best

reflect the organization needs.

Among the methods that can be applied to assess

the readiness for the market commercialization of

research and development are:

1. Methods for assessing readiness for market

commercialization of scientific developments, based

on the assessment of the innovative potential of the

organization (Claver-Cortés et al, 2018; Argyres and

Porter, 1998; Justel et al, 2007; Verena, 2005;

Sabadka, 2012; Aiman-Smith et al, 2005).

Assessment of innovative potential is a necessary

stage in the study of readiness for market

commercialization of research projects. This group of

methods is based on the assessment of the

organization's potential in terms of resource,

financial, personnel and managerial, production and

innovation capabilities of the organization itself. For

each component, a limited list of indicators is

assessed, whereas marketing indicators and an

assessment of the potential market for innovative

developments, the life cycle of scientific

developments, cooperation between participants in

the process of commercializing developments, along

with legal aspects of supporting the creation of

innovations are not taken into account. The

innovative potential of an organization can be

assessed from two positions: an assessment of the

organization's readiness to develop and implement a

specific innovative project; assessment of the current

state of the organization in relation to all or a group

of projects already being implemented.

2. Optional model (Morozov, 2012; Huixia and

Tao, 2010). The essence of the method is to calculate

the expected commercial value of the project, which

takes into account the discounted future revenues of

development, the probability of commercial success

in case of successful technical implementation,

investments in the commercialization of the project,

the likelihood of the technical implementation of the

project and investments in development. The basis for

this model usage is the results of a quantitative and

qualitative assessment of the development itself, as

well as the potential market, which are tasks with a

low level of assessment criteria formalization due to

the large number of indicators that affect the final

result. In this connection, this method does not allow

an objective assessment of the actual level of project

commercialization.

3. Hierarchy analysis method (Balykhin, 2016;

Reichert et al, 2013; Stummer et al, 2009;

Subramanian and Ramanathan, 2012; Chen and

Kocaoglu, 2008; Ishizaka and Labib, 2011). The

hierarchy analysis method is based on multi-criteria

Optimal Method Selection for Assessing the Prospects and Readiness for Market Commercialization of Scientiﬁc Researches and

Development

321

compilation of ratings of alternative options, which

makes it possible to choose the most rational solution

that satisfies a number of criteria. The advantage of

the method is the possibility of using it with

insufficient empirical data. However, comparison and

assessment of alternative options is carried out using

an expert approach, which leads to a significant

influence of subjective factors and can lead to an

erroneous decision about the prospects for

commercializing a particular project.

4. The LIFT (Linking Innovation, Finance and

Technology) methodology (Kvashnin, 2006;

Tikhonov, 2012; Assesiing Yoyr Venture, 2021) was

developed within the framework of the fifth

framework program of the European Union for

research and technological development (FP5 - Fifth

Framework Program of the European Community for

Research, Technological Development and

Demonstration Activities), conducted from 1998 to

2002. The LIFT methodology has become

widespread in assessing the relevance to the market

commercialization of research and development. The

LIFT technology audit is an expert method for

selecting innovation commercialization projects for

funding. The assessment is carried out according to

the classical scheme: collection of information

(interview) - analysis - drawing up a report. All the

information received is recorded and evaluated by

experts (in points on a scale from 1 to 5) according to

the approved indicators characterizing the project.

Indicators are divided into two categories - project

attractiveness and risk indicators.

5. The TAME (Technology and Market

Evaluation) methodology (Kvashnin, 2006;

Tikhonov, 2012) was developed by Lambic

Innovation Ltd. The difference between TAME and

LIFT methodologies is that the first focuses on

assessing potential sales markets for an innovative

product. Technology audit according to the TAME

methodology is based on a systematic approach to

assessing innovative products and their commercial

potential, and includes five sections of assessment:

strengths and breadth of market applications of an

innovative product; the essence of the new

technology used in the product; existing problems of

an innovative product commercialization; existing

problems of facilitating an innovative product

commercialization process; other commercial

matters. Each section is assessed on the basis of

questionnaires. All answers to questions are scored on

a five-point scale, but unlike the LIFT methodology,

where points are assigned only to sections (indicators)

of the assessment based on all answers to questions in

a section, in the TAME methodology each question

in a section is scored.

6. TRL methodology (Technology Readiness

Level) (Technology Management in the DOD's ATD,

2002; Forsman, 2013) is a method for assessing the

level of technology readiness for commercialization

and use in the commercial sphere, developed by the

US National Aerospace Agency NASA in the 1970s.

The levels are determined according to established

rules, taking into account, inter alia, the concept of

technology, technological requirements,

demonstration of the technological capabilities of the

product. The TRL score is expressed in natural

numbers from 1 to 9, with 9 being the highest level

corresponding to the start of commercial production

of the product. The levels have the following

characteristics: TRL 1 - Basic principles; TRL 2 -

Technological concept; TRL 3 - Experimental Proof

of Concept; TRL 4 - Laboratory verification in the

laboratory; TRL 5 - Validation of Technology in an

Industry Significant Environment; TRL 6 -

Technology Demonstrated in a Relevant

Environment; TRL 7 - Demonstration of a prototype

system in an operating environment; TRL 8 - System

completed and qualified; TRL 9 - Actual system

tested in an operating environment (competitive

manufacturing in the case of key assistive

technologies). The methodology is used by such large

companies as United Engine Corporation, United

Aircraft Corporation, Siemens, Airbus, Boeing; US

National Aeronautics and Space Administration, etc.

The literature presents dozens of different practical

applications of the TRL methodology for various

organizations, industrial companies, government

departments, national and international foundations,

which indicates the flexibility and ability to adapt the

methodology to a specific product. Despite the fact

that the TRL does not cover many aspects that should

be taken into account when assessing the project as a

whole, in practice, approaches based on the TRL

scale are used, but also describing other levels of

preparedness.

7. The TPRL (Technology Project Readiness

Level) methodology based on the TRL methodology

was developed (Petrov et al, 2016), taking into

account such project values as: Technological

readiness (TRL); Manufacturing Readiness (MRL);

Engineering Readiness (ERL); Organizational

Readiness (ORL); System Readiness (SRL); Benefits

and Risks (BRL); Market Readiness and

Commercialization (CRL) Levels. Quantitative

assessments of the TRL of a project, obtained using

the model, can be used to make various management

decisions, for example, to develop a work schedule, a

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322

financing plan, including determining the ratio of the

shares of budgetary and extrabudgetary funding

within the framework of programs implemented by

various support institutions, as well as other solutions.

8. The commercial potential of research and

development can also be assessed using classical

economic methods for evaluating the effectiveness of

investments: the Net Present Value method; Profit

ability Index method, PI; Internal rate of return

method, IRR; weighted average cost of capital,

WACC; MIRR method (modified internal rate of

return); PP method (payback period of innovation);

ARR method (innovation efficiency ratio); Break-

Even Point Analysis method (break-even point

analysis). Despite the fact that these methods

qualitatively reflect the effectiveness of an innovative

project, their disadvantage, in our opinion, is the

concentration exclusively on the financial parameters

of the project without taking into account the

technological and technical features of research and

development.

Thus, a system analysis should be a tool for

studying commercial potential. The use of various

mathematical methods makes it possible to identify

the prospects for further research, assess the level of

commercial readiness, and predict positive effects in

various fields.

To range methods for assessing readiness for

market commercialization of research and

development, it is proposed to use a number of

criteria, namely:

 initial data specification record: the method

used should take into account the most

important properties of the initial information

used to calculate the performance indicators

(the random nature of changes over time in the

technical and economic indicators of

developments, the timing of costs and future

income, the presence of non-commercial

effects in various areas);

 validity: the assessment method should be

strictly justified, logical, it should not contain

contradictions of a substantive and formal

nature (economic, mathematical, technical,

etc.);

 unambiguous results: the method should

provide an unambiguous interpretation of the

results of the application, not allow

conditional transitions;

 informative content: one of the most important

requirements for methods. The higher the

informative content level, the lower is the

likelihood of an erroneous decision, the lower

is the risk of the need for additional research;

 accuracy: the criterion is primarily important

for methods that do not give a qualitative

assessment of the possibility of market

commercialization, but provide quantitative

information for decision making;

 simplicity: the complexity of the method used

should be related to the expected results;

 information accessibility: the main problem in

assessing the readiness for the market

commercialization of research and

development is the lack of information or the

difficulty of obtaining it. This is primarily

about the effect (income part) of investments.

In many cases, it is practically impossible to

determine it precisely, while it is necessary at

the initial justification stages of the

commercialization possibility;

 implementation costs: the complexity of the

assessment, the need for additional financial

costs when applying certain methods of

assessing the readiness for market

commercialization of research and

development.

Thus, it is proposed to compare the tools available

to the organization for assessing the commercial

potential of research and development according to

the following criteria: initial data specification record,

validity, unambiguous results, informative content,

accuracy, simplicity, information accessibility,

implementation costs.

According to the proposed criteria and objects

(methods), a survey of experts was carried out, in the

capacity of which, in the course of the analysis, were

experts in the field of assessing the effectiveness of

innovations. Namely, PhDs of four higher

educational institutions of the Russian Federation: 2

doctors of technical sciences, 12 candidates of

economic sciences. Moreover, IT managers of four

domestic enterprises took part in the survey. A total

of 20 people were interviewed (the minimum

allowable sample size).

The results of the survey of experts are presented

in table 1.

Optimal Method Selection for Assessing the Prospects and Readiness for Market Commercialization of Scientiﬁc Researches and

Development

323

Table 1: Results of the survey of experts.

Criterion

Objects (methods)

1. Assessment of

organization

innovative potential

2. Optional model.

3.Hierarchy

analysis method

4. LIFT

5. ТАМЕ

6. TRL

7. TPRL

8.Standard methods

initial data specification record:

considers (1) —

does not consider (5)

5 3 2 2 2 1 1 4

validity:

high (1)

—

low (5)

4 2 3 1 1 2 1 2

unambiguous results:

(

)

—

low

(

)

5 2 3 2 1 1 1 1

informative content:

high (1)

—

low (5)

4 3 3 3 2 2 1 3

accuracy:

high (1)

—

low (5)

5 4 3 2 1 2 1 3

simplicity:

(

)

—

low

(

)

1 3 3 3 4 4 5 3

information accessibility: full (1) — partial (5)

1 3 2 3 4 4 5 2

implementation cost:

(

)

—

low

(

)

1 4 3 4 4 4 5 3

The numerical values in the table are essentially

objects of a non-numerical nature, since they only

reflect the attitudes of experts such as "good",

"normal", "bad". An expert, putting down a score,

compares objects, but the ratio between the scores

does not answer the question “How much better /

worse? » So A. I. Orlov notes that «A common

misconception is that experts try to consider the

answers as numbers, they are engaged in 'digitizing'

their opinions, attributing numerical values to these

opinions - points, which are then processed using the

methods of applied statistics as the results of ordinary

physical and technical measurements. In the case of

arbitrariness of "digitization", the conclusions

obtained as a result of data processing may not be

relevant to reality» (Orlov, 2002).

In general, on the basis of the expert assessment

data, the task is to compose the average ordering,

which is the closest to the true one, based on the data

set by the ordering experts. To do this, we will use the

Kemeny-Snell median. The choice of the median for

the analysis is based on the fact that the Kemeny

median is the only resultant strict ranging that is

neutral, consistent, and condorcet.

𝑟



In the algebraic approach, the main task is to

determine the distance between two permutations, for

example, АиВ - d (А, В). For each permutation, a

matrix is determined, whose elements are the

numbers +1 or 0. The element of the matrix with

number (i, j) is +1 if the range of object i is less than

the range of object j, that is, if object i comes in

ordering before object j. Otherwise, this element is

equal to 0. The diagonal elements of the matrix can

be omitted. Let us denote 𝑎



 such a matrix

constructed from the permutation A, 𝑏



 - by the

permutation B. Now the distance d (A, B) introduced

by Kemeny and Snell is:







ijij

baBAd

),(

(1)

Using this distance, it is possible to determine

something like the "center" of all the opinions

expressed, choosing as such a permutation, the sum

of the distances from which to all expert permutations

𝐴



,...,𝐴



is the smallest. This permutation 𝐴



called the Kemeny-Snell median. So, a permutation

𝐴



is called the Kemeny-Snell median of the set of

permutations

AA,...,

if:







AAdAAd

),(min),(

(2)

Calculation 𝐴



in the case of large m, n can

present certain difficulties.

The algorithm for evaluating methods includes

the following steps:

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324

1. Based on the set goal of asessing the methods,

we select a set of informative quality indicators {k_1,

k_2, ...., k_m}, which will be used to evaluate the

quality of each object from the set OB_j = ⟨Ob_1,

Ob_2, ..., Ob_n)

In other words, we need to assess the 8 methods

discussed above by eight indicators: k1 - initial data

specification record; k2 - validity; etc. All indicators

were evaluated in points on a scale from 1 to 5. At the

same time, 1 indicates the best value of the indicator,

whereas 5 - the worst.

2. We range the objects for each line

corresponding to one of the indicators. Each j-th

indicator will give its own vector of preferences 𝑘





𝑘



,𝑘



,...,𝑘



, 𝑗  1, 𝑚, where 𝑘



is the ordinal

number of the object occupying the i-th place in the

ranпing according to the j-th indicator.

The initial data of a survey of experts for analysis

using the Kemeny median are presented in Table 1.

3. Let's predetermine all assessments of objects in

an ordinal scale and find out whether preference can

be expressed by ranges. In each ranging, the first

place is occupied by the most attractive, from the

point of view of the considered indicator, the object,

and then in descending order. Then, each vector kj is

associated with a vector 𝜋



𝜋



,𝜋



,...,𝜋





formed according to the rule: coordinate 𝜋



is the

number of directions, which, according to the j-th

particular indicator, are more preferable than the

direction with the ordinal number i (Tikhonov, 2012;

Mitus and Katsko, 2015). The results are summarized

in Table 2.

Table 2: Assessments of objects in an ordinal scale.

Criteria

Initial data

specificatio

n record

7 5 2 2 2 0 0 6

Validity 7 3 6 0 0 3 0 3

Unambiguo

us results

7 4 6 4 0 0 0 0

Informative

content

7 3 3 3 1 1 0 3

Accuracy 7 6 4 2 0 2 0 4

Simplicity 0 1 1 1 5 5 7 1

Information

accessibility

0 3 1 3 5 5 7 1

Implementa

tion cost

0 2 1 2 2 2 7 1

4. Search for group ranging that will best

represent individual preferences. As such, the

Kemeny median will be considered, defined as

follows:







,min*





(3)

where







is the distance between the two

rangings, determined by the formula:











(4)

5. Next, we build a loss matrix 𝑅𝑟



: we

consider vectors in which the direction with a number

𝑖



𝑖∈



1,2,....𝑛





is located sequentially from the 1st

to the nth place: 𝜋𝜋



,𝜋



,....,𝜋



,....,𝜋



 -

ranging, in which the p-th indicator is in the q-th place

𝜋



𝑞1 (i.e.), then :







pppq



(5)

For our data, we get the matrix of losses in Table

Table 3: Loss matrix R.

35 33 31 29 27 25 23 21

27 19 13 9 11 15 21 29

24 16 14 14 16 20 24 32

17 11 7 9 15 23 31 39

15 13 13 17 21 25 33 41

18 14 12 14 18 22 30 38

21 23 25 27 29 31 33 35

19 13 13 13 17 23 29 37

Obtained by the author based on the research results.

6. By minimizing the functional, we solve the

assignment problem:

























,1,1

min*

pqpq

nqx

npx

(6)

where X is a binary matrix of values: x

= 1 if the

pth alternative is assigned to the qth place and xpq =

0, otherwise.

When conditions (6) are met, the matrix







corresponds to some ranging.

We get the assignment matrix in the form (Table

4):

Optimal Method Selection for Assessing the Prospects and Readiness for Market Commercialization of Scientiﬁc Researches and

Development

325

Table 4: Assignment matrix.

0 0 0 0 0 0 0 1

0 0 0 0 0 1 0 0

0 0 0 0 0 0 1 0

0 0 0 1 0 0 0 0

0 1 0 0 0 0 0 0

0 0 1 0 0 0 0 0

1 0 0 0 0 0 0 0

0 0 0 0 1 0 0 0

Using the matrix 𝑋

𝑥



 , we restore the

vector of group preference K *, analyzing the matrix

row by row: if, then in the vector K * we put. In our

case: 𝑥



1; 𝑥



1; 𝑥



1; 𝑥



1; 𝑥



1;

𝑥



1 ; 𝑥



1 ; 𝑥



1; ; hence, 𝑃





7,5,6,4,8,2,3,1



5 DISCUSSION

Kemeny's median method made it possible to range

the methods for assessing the readiness for the market

commercialization of research and development. The

calculation results gave grounds to prioritize the use

of the methods:

1. TPRL Methodology.

2. Methodology TAME.

3. TRL Methodology.

4. LIFT Methodology.

5. Economic methods for assessing the

effectiveness of investments.

6. Optional model.

7. Hierarchy analysis method.

8. Methods for assessing readiness for market

commercialization of scientific developments, based

on the assessment of the innovative potential of the

organization.

As the results of our research have shown, the

TPRL methodology is the most optimal method for

assessing the readiness for market commercialization

of research and development, as well as assessing

their commercial potential. Despite the priority of this

method, in our opinion, it requires additional labor,

since many factors in the proposed model are

subjective, which ultimately can distort the results of

evaluating the commercialization of scientific

developments and reject promising developments at

the initial stages.

Therefore, the prospect for further research is the

modernization of the classic TPRL model, which will

cover the main factors and criteria inherent in the

scientific development of universities.

6 CONCLUSIONS

Analysis of modern methods for assessing the

prospects and readiness for market

commercialization of research and development of

universities, taking into account these projects

specifications, allowed us to reasonably select the

main criteria for ranging them in order of importance.

On the basis of Kemeny's median method, these

methods were ranged, which made it possible to

determine the most optimal method for assessing the

readiness for market commercialization of research

and development, as well as assessing their

commercial potential, which is the TPRL

methodology, however, in our opinion, it requires

additional modernization, because it does not

sufficiently take into account the main factors and

criteria inherent in the scientific development of

universities, which is a prospect for future research.

ACKNOWLEDGEMENTS

The study was carried out with the financial support

of an internal grant from FSAEI HE "Sevastopol State

University" within the framework of scientific project

No. 34 / 06-31.

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