APPLYING THE DISTEH METHOD TO ASSESS THE FIRM’S
INNOVATION POTENTIAL: A ROMANIAN CASE STUDY
Dr. Cezar Scarlat*, University “Politehnica” of Bucharest, Romania
cezarscarlat@yahoo.com, *corresponding author
Dr. Catalin Alexe, University “Politehnica” of Bucharest, Romania
cataalexe@yahoo.com
Dr. Eugen I. Scarlat, University “Politehnica” of Bucharest, Romania
eugen.scarlat@ancs.ro
Catalina Daraban, University “Politehnica” of Bucharest, Romania
cmcalaras@yahoo.com
ABSTRACT
Lots of research work is focused on innovation. The theory is based on concepts as:
innovation, innovative individuals or organizations, innovation potential / capacity,
innovation capability. The practice is centered on innovation assessment or audit, and
innovation management. In the process of designing the company strategy, it is critically
important that top management becomes familiar with the competitive advantage of their
company in the area of innovativeness – as the innovation capability has a leverage effect: if
applied, the competitive advantage is considerably amplified.
Based on the authors recent research work on innovation potential of the small and medium
size firms, the paper aims at applying the DISTEH method for assessing the firm’s innovation
potential. This method was successfully applied in the case of a Romanian firm active in the
media industry. The results prove to be useful for the company managers who are making
decisions to enhance its innovation potential and, therefore, competitiveness.
The implications are of high importance for practitioners (entrepreneurs and managers) as
well as for the researchers and academics interested in developing tools to assess the firm’s
innovation potential.
Keywords: innovation, innovation potential assessment, DISTEH method, Romania
INTRODUCTION
Innovation potential may be assessed either at macroeconomic or microeconomic levels. As
example, the MERIT Centre (Maastricht Economic and social Research and training centre
on Innovation and Technology) is publishing studies on innovation in the European Union
Member States (MERIT, 2008). However, most of the research and literature is focused on
the company as the innovation generator.
Any company has a potential to be creative and innovate. According to Goffin and Mitchell
(2005), the innovation drivers are: changes in the clients’ needs, changes in the business
environment, growing competition, and new technologies.
Innovation is a complex process (Rüggeberg, 2008); its theory is based on concepts as:
innovation, innovative individuals or organizations, innovation potential / capacity,
innovation capability. Innovation was defined by prestigious scholars (Kuhn, 1985; Wolfe,
1994; Drucker, 2000; Wolpert, 2002) – to name just a few.
The practice is currently centered on innovation assessment or audit, and innovation
management. The process of innovation assessment is known as innovation audit as well,
mainly in the German school (Eckelmann, 2002; Herstatt et al., 2007). In the process of
designing the company strategy, it is critically important that top management becomes
familiar with the competitive advantage of their company in the area of innovativeness – as
the innovation capability has a leverage effect: if applied, the competitive advantage is
considerably amplified. Such companies are well-known for their excellence in innovation
(Warschat, 2005) or innovation excellence (Nilsson et al., 2010). The innovation capability,
intimately linked with the entrepreneurial capabilities (Alvarez and Barney, 2000), is
assessed in order to provide strategic tools for companies’ managers.
The focus of this paper is to test the use of the DISTEH method (Scarlat, 1980, 2000, 2005c)
for assessing the firm’s innovation potential – in the framework of a more comprehensive
model for assessing, analyzing and continuously improving the firm’s innovation capability
(Alexe, 2010). Assessing the innovation potential is just a stage of this complex process.
Based on the authors’ recent research work on innovation potential of the small and medium
size firms (Scarlat and Alexe, 2010), the paper present the results of applying the DISTEH
method for assessing the innovation potential of a Romanian small business. The strengths of
the method are highlighted – as it has previously applied to investigate innovative
technologies as well as technology prediction (Scarlat 2004, 2006). The method was
successfully applied in the case of a Romanian firm active in media industry and – according
to the – seven groups of innovation factors were analyzed (conceptual – firm’s philosophy
on strategy, company culture, organization, personnel, technology, learning capability,
economic and financial performance) comprising 95 criteria as a total.
The results of the experiment prove to be useful for the firm’s managers who have made
decisions to enhance its innovation potential and, therefore, the firm’s competitiveness. The
implications are of high importance for practitioners (entrepreneurs and managers) as well as
for the researchers and academics interested in developing tools to assess the firm’s
innovation potential.
The remaining of this paper is structured as follows: Assessment of the firm’s innovation
potential; DISTEH method, Case study: The Company IMG, Conclusions.
ASSESSMENT OF THE FIRM’S INNOVATION POTENTIAL
In March 2011, Google search for “innovation potential” has generously offered approx.
5,000,000 items in 0.22 seconds and for “innovation capability” displayed in 0.25 seconds
only 2.600.000 items!
In order to avoid any confusions, for the needs of this study, it is agreed that the concept of
‘innovation capability’ is larger than ‘innovation potential’: as described by Alexe (2010), the
model for assessing and continuously improving the firm’s innovation capability is a ten-
stage process – in which the assessment of the firm’s innovation potential is one of the stages
only (Table 1). The model is an adaptation of the methodology of the Fraunhofer Institut
(2007) to improve innovation capability while the method to assess the firm’s innovation
potential is largely inspired by the methods developed by Eckelmann (2002) and Arthur D.
Little (2002). The main features of this process are summarized in Table 1.
Table 1: Model for assessing and continuously improving the firm’s innovation capability.
No.
Stages
Content briefly
Participants
Stages, activities, timing, outcomes
Top management
1. Planning stage
Participants
Data collection, questionnaire-based
Design the company innovation profile
Define the company
profile
Assess the managers’ and Surveys questionnaire-based:
- addressed to managers
employees’ attitude
- addressed to employees
towards innovation
Analyze the innovation factors and
Assess the company’s
criteria
innovation potential
Management
5.
Feedback to the company
management
Management
6.
7.
Design the innovation
balanced scorecard
Analyze possible
solutions to improve the
innovation capability
8.
Action planning
9.
Implementation of the
action plan
Progress evaluation
2.
3.
4.
10.
Calculation of the scores of the
innovation potential – by factors and
overall
Analysis of the disagreements and
conflicts
Benchmarking
Presentation of the results of the
innovation potential assessment: scores of
the innovation potential – by factors and
overall; disagreements and conflicts;
position – relative to the competition
Design a comprehensive set of indicators
– to monitor the innovation process
Management
Employees (partly)
Management
Employees (partly)
Management
Explore and identify possible solutions
Decide on the best solutions – according
to the firm’s strategy
Decide on the intervention areas and
methods
Design the set of measures / solutions to
improve the innovation capability
Planning of the associated actions
Implement the plan (measures / solutions)
Top management
Re-calculation of the scores of the
innovation potential – by factors and
overall
Assess the efficiency of the solutions
(effects noticed after 6 months at least)
Resume the process and continue →
Managers
Employees (partly)
Top management
Project teams
The authors have tested and improved the above model and methodology as well as the
method to assess the firm’s innovation potential (Alexe, 2009; Scarlat and Alexe, 2010;
Alexe et al., 2010; Scarlat et al., 2010).
The focus of this paper is on the fourth stage – assessing the company’s innovation potential,
(Table 2) assuming that:
(i)
this stage is just a component of the larger process of improving the firm’s
innovation capability – which assumes that the company innovates needs-based,
(ii)
innovation is part of its strategy; there is an innovation culture in place; the
company continuously implements and learns out if its innovation actions
(Lercher, 2008);
the factors and criteria presented in Table 2 are the result of thorough analysis
aiming at identifying the significant elements that define the innovation potential.
Table 2: Innovation potential assessment – factors and criteria (Alexe, 2010).
No.
Factors
No. of criteria
Examples of criteria
Environment strategic analysis
1. Strategy philosophy
15
2.
Company culture
12
3.
Organization
16
4.
Personnel
15
5.
Technology
12
6.
Learning capability
16
7.
Economic and financial
performance
9
Forecast exercises
Vision
Mission statement does include innovation
Innovation strategy
New products marketing strategy
Resources allocated for innovation
…
Innovation culture
Openness (outward)
Conflict resolution
Leadership style
Risk orientation
Attitude regarding the mistakes made
…
Hierarchy
Flexible structures
Delegation
Decision autonomy
Information flows
Communication efficiency
Decision making process
Teamwork
…
Training
Promotion
Change in organization
Creative employees
Financial motivation
Non-financial motivation
Focus on creative individuals
…
Technology know-how
Patents
Focus on technology change
Methods to assess innovative ideas
IT and dedicated software
Benchmarking
…
Knowledge access
Best practice
Lessons learnt
Involving clients in the learning process
Involving suppliers in the learning process
Sharing knowledge with others
Relationships with consulting firms
Relationships with R&D, HE institutions
…
System to measure innovation activity
System to register innovative ideas
Indicators to measure innovation
Innovation budget
…
Total number of criteria
95
-
To note that each criterion implies actually a question or a set of questions; some examples
follow:
(i)
the “Environment strategic analysis” criterion should read as “Is the company
running environment strategy-type analyses (on regular basis)?”
(ii)
the “Knowledge access” criterion should read as “Do the company’s employees
have access to the company’s knowledge database? Is there a system in place to
disseminate the knowledge among employees?”
(iii) the “Indicators to measure innovation” criterion should read as “Does the
company have a system of indicators to measure innovation and innovative
activities, in place?” and so on.
The system is open in that sense that new criteria might be added if necessary; this might
happen if a certain criterion generates more questions. For example: the criterion (ii) above.
Each factor is assessed criterion by criterion, as a percentage, independently, according to the
IPAM (Innovation Potential Assessment Method) complex multi-interviewing procedure
(Alexe, 2010). The results are summarized using an assessment fiche: Table 3 displays – as
example – the matrix of a such fiche, used in the case of “Economic and financial
performance” innovation factor.
Table 3: Innovation factors assessment fiche – “Economic and financial performance” factor:
Calculation of the innovation potential score.
Evaluation scale, p [%]
0
25
50
75
100
No
A
few
Partial
Clear
Complete
No.
Innovation criteria
evidence
‘Never
happens’
1.
2.
3.
…
9.
evidences evidences
‘Sometimes
‘Balanced’
happens’
evidences
‘Usually
happens’
evidences
‘Always
happens’
System to measure innovation activity
System to register innovative ideas
Indicators to measure innovation
Innovation budget
Total number of answers
i=1
i=2
i=3
i=4
i=5
n1
n2
n3
S(F7)
n4
n5
Score of the innovation potential
F7 is the innovation factor number 7 (per Table 2).
S(F7) is the score of the innovation potential associated to the firm’s “Economic and financial
performance” – calculated as follows:
S(F7) = (Σi ni pi) / (Σi ni)
where:
i = 1, 2, …, 5
ni = number of answers associated to each percentage
(1)
pi = percentage (i) i.e. 0%, 25%, ..., 100%
Σi = summation symbol, by i, from 1 to 5
A legitimate question (why the number of criteria is different – it varies from factor to factor)
is addressed by using comparable measurement systems (as percentage). Consequently, the
number of criteria is neither a limitation nor a limit; the design is open, new criteria might be
added if considered necessary. However, deleting criteria is a huge mistake because
disregarding a certain criterion (then a specific element related to innovation) is going to alter
(lower) the score of the innovation potential.
A significant strength of the IPAM is the analysis of the divergences or even conflicts
identified among opinions expressed by the interviewees (Table 4).
Table 4: Innovation factors assessment fiche – “Economic and financial performance” factor:
Analysis of the conflicts in opinions (an example).
Evaluation scale, p [%]
0
25
50
75
100
No
A
few
Partial
Clear
Complete
No.
Innovation criteria
1.
2.
3.
…
9.
System to measure innovation activity
System to register innovative ideas
Indicators to measure innovation
Innovation budget
Legend
evidence
‘Never
happens’
●▲
●□▲♦
▲
evidences evidences
‘Sometimes
‘Balanced’
happens’
●
evidences
‘Usually
happens’
evidences
‘Always
happens’
♦
□
▲
□●♦
♦□
● = respondent A; □ = respondent B;
♦ = respondent D; ...
▲ = respondent C;
In principle, different cases are possible:
- strong disagreement (on the “system to measure innovation activity”);
- strong agreement that the “system to register innovative ideas” is a weakness; here is
a lot of room to improve the innovation potential;
- agreement that the “indicators to measure innovation” is a strength, an innovation
advance;
- relatively limited disagreement (on the “innovation budget”).
Each case or situation is managed by specific means; it should be underlined that the
innovation consultant plays a key-role.
After assessing all factors, the firm’s innovation potential is measured by the overall score of
innovation potential S(IP):
S(IP) = Σj S(Fj) / 7
(2)
where:
j = 1, 2, …, 7 (the total number of innovation factors considered)
Fj = innovation factor j
S(Fj) = score of the innovation potential associated to the factor Fj
Σj = summation symbol, by j, from 1 to 7
The major critique addressed to this method is that the score itself – regardless how high or
low is – does not offer decision support or image of the innovation potential of the company.
For example: a company reporting a score like S(IP) = 49% is it good? Is it worse than
another company with 55% innovation potential score? How innovative is our company
overall?
DISTEH DECISION MODEL AND METHOD
It is extremely important for the company decision makers to have practical and operational
tools to assess, analyze and rank their products according to their performance – compared
with similar products of their competitors, which is, basically, to apply multi-criteria decision
making models. The Neumann and Morgenstern’s Utility Theory is probably the most
extensively used method to make multi-criteria decisions; since then (1944) lots of
improvements were reported. Romanian school of industrial management made notable
efforts in the area of developing new models to rank the industrial products according to their
performance – compared with similar products of the competition.
Originally the DISTEH method was developed as decision model to assess the products’
technical performance – as displaying some advantages compared to other decision methods
(Scarlat 1980, 1981, 1987, 2000). The method was developed as a tool to assess the level of
technical performance of products (goods or services) and technologies, within laboratories
of Industrial Management Department from University “Politehnica” of Bucharest, Romania.
The method was originally named “DISTEH” (Costake and Scarlat 1981, 18). The influence
of time factor is considered first time by Costake and Scarlat (1985: 226, 233). DISTEH
method was tested in a number of practical training, consulting and research circumstances
and continuously improved; it is actually a multi-criteria decision-making model (Scarlat
2005c), and some of its major applications are addressed to products’ competitiveness
analysis (Scarlat 2004, 2005b, c), marketing pricing strategies (Scarlat 2004, 2005b),
technology analysis (Scarlat 2004, 2005a) or technology prediction (Scarlat 2006). The
flexibility of the method is tested in this case in a different area: assessing the innovation
potential – considered a multi-criteria decision situation.
The basic DISTEH model: Absolute ranking
Assuming that any given decision option Ai (i = 1 to m; m = number of the available decision
options) is characterized by a set of characteristics (criteria for assessing the innovation
potential, in this case) Cj (j = 1 to n; n = number of criteria), one can define the performance
matrix:
C = [cij]
(3)
where: cij is that value of the criterion Cj in the case of the option Ai.
In this case, the decision options correspond to the firms for which the innovation potential
assessment is conducted. Then an important aspect is highlighted: the assessment does have
sense only in a larger context (the industry in which the targeted company is active). This
also means that data about the firms active in this industry should be available and a
consistent database should be developed. All these elements characterize a mature, well
developed business environment.
It is also understood that – for each company (i): a key-performance indicator (pi) and the
time of assessment (ti) are known as well.
The purpose is to determine a unique value associated to each firm Ai ; this value is expected
to describe the firm’s innovation potential.
One can define an ideal firm (I) – in terms of its innovation potential, real or virtual – having
the best criteria cIj, as follows:
cIj = maxi (cij) when criterion Cj is to be as high as possible
cIj = mini (cij) when criterion Cj is to be as low as possible
(4)
(4’)
Note that (I) describes, generally, a virtual company. Its coordinates may vary in time but – if
the analysis horizon is relatively short – the position of (I) is considered as time-stable
(Scarlat 2000, 372).
The key-idea is that each company (i), either real or virtual, can be represented as a point in
n-dimensional space. The closer the point is to (I), the better the firm – in terms of its
innovation potential. Thus, it makes sense to define, for each company, the innovation
potential distance (ex technical distance) between the targeted firm and the ideal one, as:
 c ij  c Ij
b j

c Ij
j 1 
n

IPi 




2
(5)
where: bj is associated with the importance of the criterion Cj; and bj weights the criterion Cj
(0 < bj < 1).
The firms are ranked starting from the best one as innovation potential (minimumIPi). Note
that the innovation potential distance is zero in the case of the ideal firm as innovation
potential (IPI = 0). Bigger theIPi value, lower the innovation potential of the company Ai
and most probably its overall performance. In other words, for any given firm Ai (i = 1 to m),
one might calculate a unique value associated to that firm IPi, value that allows the ranking
of all the companies considered (starting with the best on the top).
Note that if only one company is assessed then the analysis makes sense as well because the
ideal might be defined, by different techniques (e.g. benchmarking-type).
DISTEH model: Relative ranking
The DISTEH method can also apply when the decision maker needs to select not the
absolutely best firm but the relatively best firm, in a similar manner (Scarlat 2000, 372-373).
The formula is slightly different (6): only “D” (”Desired”) replaces “I” (“Ideal”).
 c ij  c Dj
b j

c Dj
j 1 
n
IPDi 





2
(6)
The “desired” firm does not have necessarily the best features. The coordinates of the D
point/firm are decided usually by the customer, not by the decision maker.
Self-calculation of the weight coefficients
When necessary and/or required, all decision-making methods consider the weight
coefficients (bj). And almost all methods estimate bj values subjectively. Only when those
values are the result of well-conducted (marketing) surveys, the decision making process is
fair. Most methods assess the weight coefficients (bj), subjectively. A much simpler approach
is used by DISTEH method: each of the weight coefficients bj is calculated based on
dependency reported by each of the P(Cj) linear regression curves (Scarlat 1987, 285, 287):
m
mj 
m
m
m  cij pi   cij  pi
i 1
i 1
i 1
2


m  c    cij 
i 1
 i 1 
m
m
(7)
2
ij
and
bj 
mj
(8)
n
m
j 1
j
where:
P = [pi] is the vector of firm performance
Cj = [cij] is the vector of values of the criterion Cj (j = 1 to n) for all the firms (i = 1 to m).
The signum of mj has its own significance: “+” identifies “high features” (4) and “-“ points
“low features” (4’).
Identifying the Critical Characteristic
The Critical Characteristic (CC) defines that criterion, which worsens the firm’s innovation
potential (makes the corresponding value IPi too high). CC could be easily identified - as
corresponding to:
 c  c  2 

ij
Ij
 
max  b j
(9)


j
c
Ij

 
respectively
 c  c  2 

ij
Dj
 
max  b j
(9’)

j
cDj  


Once identified, CC must be improved: “Improving the CC” would be the major task for the
consulting team working with the target company top management and R&D department.
The improving process is continuous: when CC completes its “improving potential”, the
next-in-line criterion follows.
Usually, the ranking depends on the weights. However, there are cases – both in theory and
practice – when the ranking of two options remains unchanged, for all the possible values of
their respective weights (0 ≤ bj ≤ 1) or, at least, for large variation intervals. Such analysis is
presented in (Scarlat 1981).
To conclude, the DISTEH method is a useful tool to assess the firms’ innovation potential
and rank them accordingly, objectively. Based on the same model, the firm’s overall
innovation capability can be improved by setting research priorities – corresponding to the
most sensitive criteria.
CASE STUDY: THE COMPANY IMG. RESULTS AND DISCUSSION
The applicability of the DISTEH method for assessing the innovation potential of companies
was tested in the case of a Romanian company active in media industry (IMG) which was
already analyzed in terms of its innovation capability, and its innovation potential was
already assessed by a ‘control’ method (IPAM) – as previously described by formulas (1) and
(2).
It is worthy to mention that both methods were developed by the authors (IPAM by Alexe
and DISTEH by Scarlat), first as a dedicated method, second as a multi-purpose decision
tool. Just anecdotally: while IPAM is an image of incremental innovation, the use of DISTEH
for assessing the innovation potential corresponds to a disruptive innovation.
Under same hypotheses (assuming that the factors and criteria presented in Table 2 are the
result of thorough analysis aiming at identifying the significant elements that define the
innovation potential; and based on the same results of the analysis – same consequences per
each criterion) the comparative results are depicted in Table 5. The assessment of the firm’s
innovation potential was a part of the more comprehensive analysis of the firm’s innovation
capability which was conducted in 2010-2011.
Table 5: Model for assessing and continuously improving the firm’s innovation capability.
DISTEH
No.
Innovation factors
IPAM [%]
1
Absolute
Relative2
3
1. Strategy philosophy
58.88 (V)
0.0587 (V)
0.0445 (V)
2. Company culture
63.88 (VII)
0.0516 (VII)
0.0516 (IV)
3. Organization
59.37 (VI)
0.0580 (VI)
0.0295 (VII)
4. Personnel
40.00 (II)
0.0857 (II)
0.0857 (II)
5. Technology
45.19 (III)
0.0783 (III)
0.0426 (VI)
6. Learning capability
54.16 (IV)
0.0655 (IV)
0.0655 (III)
7. Econo-finance performance
18.51 (I)
0.1164 (I)
0.1164 (I)
Overall score for innovation
48.57
0.2019
0.1803
potential
1
To the ideal [100%; 100%; 100%; 100%; 100%; 100%; 100%]
Relative to a desirable profile of innovation potential [90%; 100%; 80%; 100%; 75%; 100%; 100%]
3 The priority ranks are given in brackets (parenthesis)
2
Both methods offer the same results – in terms of priority ranking: both point at “economic
and financial performance” as the factor that damage the firm’s innovation potential the most
(only 18.51% innovation potential / 0.1164 maximum distance from the ideal point of
innovation potential). And the “company culture” is the most advanced innovation factor for
the company IMG.
The results in both methods are non-dimensional. However, it should be noted that DISTEH
values are distances to the ideal point of innovation potential: lower the value, shorter the
distance, better – see formula (5).
Both methods allow watching the dynamics of the innovation potential (how the score
evolves in time – calculated periodically).
Results are presented in case of non-weighted criteria and factors. The results are not
changing significantly in the case of considering weighted criteria and/or factors. However,
there are twofold advantages of the DISTEH method in this respect:
- it allows the objective self-calculation of the weights;
- it allows direct correlation between firm’s innovation criteria, factors, and potential –
on one hand – and firm’s key-performance indicators.
The latter is actually a direction of further research.
The higher potential of the DISTEH method is evident when DISTEH is relatively calculated
(6). The relative point is the desired level of innovation potential factors, to be reached in the
future. Those target levels (which might differ from 100%) are established by benchmarking
methods, using adequate database. In the case of the company IMG analysis, a top competitor
was surveyed and its levels of innovation potential factors assessed accordingly. The results
are changing in that sense of priority setting: some of the innovation potential factors are
unchanged as priority (I and II) while others are changing; the IMG’s “strategy philosophy”
keeps its rank (V) just by accident.
The implications for the IMG top management are of substantial importance: as priorities are
changing, the actions are different – following to the ranking determined by calculating the
relative technical distance. And so are the associated cost, and the expected efficiency of the
efforts to improve the IMG’s innovation capability. Currently, this process is in full progress.
IPAM has the advantage of simplicity and directness. DISTEH is more sophisticated as the
calculus is little bit more complex. The trade-off is that DISTEH has a higher potential
offering more information for the firm’s decision makers.
CONCLUSIONS
The firm’s innovation potential assessment is a necessary exercise – part of the firm’s process
to improve its innovation capability, and – supposedly – its competitiveness and overall
performance.
Assuming that the analysis of the innovation factors and inventory of the innovation criteria
is fairly conducted, the need for improving the firms’ innovation capability could be satisfied
using IPAM and DISTEH methods for assessing the firm’s innovation potential.
The use of the DISTEH model and method for assessing the innovation potential was
validated – its outcomes resonating to the IPAM results.
Both methods offer reliable and coherent results, and both could be used for examining
companies’ dynamics in terms of innovation potential. However, IPAM is more intuitive (as
percentage is calculated), more direct and simple that the more complex DISTEH, although
the latter has a higher potential offering more information for the firm’s decision makers.
In any case, there are critical prerequisites: quality consulting services, quality databases – by
industry and own firm, which allow benchmarking studies, dynamics analyses and alike as
reliable background for sound strategic decisions.
When the target is specifically set by benchmarking techniques or other reasons-based, then
the assessment of the innovation potential, and the actions to improve the company’s
innovation capability must be conducted by use of DISTEH and calculating the relative
technical distance of the innovation potential.
The IMG case study (assessment of the innovation potential of a Romanian company active
in the media industry) reveals important implications for firms’ top management: choosing
the appropriate method (as DISTEH associated to benchmarking techniques to calculate the
relative technical distance) impacts the firm’s priorities, actions, and – consequently – the
associated cost, and the expected efficiency of the firm’s efforts to improve its innovation
capability.
The results of the experiment prove to be useful for the firm’s managers who have made
decisions to enhance its innovation potential, innovation capability and, therefore, the firm’s
competitiveness. The implications are of high importance for practitioners (entrepreneurs and
managers) as well as for the researchers and academics interested in developing tools to
assess the firm’s innovation potential, continuously.
REFERENCES
1. Alexe, C.G. (2009). The analysis of innovation capability at the level of firm. Proceedings
of the fourth International Conference of Management and Industrial Engineering –
ICMIE 2009, 5-6 November 2009, Bucharest. D. Dumitriu (Ed.): Management in the
Worldwide Contemporary Challenges. Bucharest: Ed. Niculescu. 168-176.
2. Alexe, C.G. (2010). Valorificarea potentialului inovativ al firmelor mici si mijlocii /
Valorization of the SME innovation potential. PhD Thesis. Bucharest: University
“Politehnica”.
3. Alexe, C.G., Scarlat, C., Alexe, C.M. (2010). Improving the innovation management in
Romanian SMEs. Proceedings of the 5th International Conference on Business Excellence
(vol.1), 15-16 October 2010, Brasov, Romania. C. Bratianu, D. Lixandroiu, N.A. Pop
(Eds.): Business Excellence, Vol.1. Brasov: Infomarket Publishing House. 10-13.
4. Alvarez, S., Barney, J. (2000). Entrepreneurial Capabilities: A Resource-Based View.
G.D. Meyer and K.A. Heppard (Eds.): Entrepreneurship as Strategy. London: Sage
Publications.
5. Arthur D. Little (2002). Die Innovation Scorecard. European Business School. Retrieved
from: http://www.innovation-scorecard.de.
6. Costake, N. and Scarlat, C. (1981). Determinarea nivelului tehnic al produselor. Revista
economica. March 1981, 13. 16-18.
7. Costake, N. and Scarlat, C. (1985). Analiza nivelului tehnic al produselor / Analysis of
the products’ technical performance. Revista Automatică-Management-Calculatoare
AMC Journal. 47, 225-36. Bucharest: Ed. Tehnica.
8. Drucker, P. (2000). Inovare si spirit intreprinzator. Bucharest: Ed. Teora.
9. Eckelmann, O. (2002). Die Innovation Scorecard als Instrument des Innovations- und
Technologiemanagements - Möglichkeiten und Grenzen, Diplomarbeit. European
Business School, Schloß Reichartshausen am Rhein.
10. Fraunhofer-Institut für System- und Innovationsforschung (2007). Überholspur
Innovation Messung, Bewrtung, und Steigerung der Innovationsfӓhigkeit durch
www.innoscore.de
11. Goffin, K., Mitchell, R. (2005). Innovation management: strategy and implementation
using the pentathlon framework. Palgrave Macmillan.
12. Herstatt, C., Buse, S., Trapp, S. (2007). Leistungsmerkmale eines KMU-gerechten
Innovationsaudits. Hamburg: Technische Universität Hamburg - Hamburg Institut für
Technologie- und Innovationsmanagement.
13. Kuhn, R. (1985). Frontiers in Creative and Innovative Management. Cambridge, MA:
Ballinger.
14. Lercher, H. (2008). Innovationen. Serienmӓssig. IMG Innovation-Management-Group,
Consulting Management Research. Retrieved from:
www.innovationsmanagement.at/_.../08IMGKurzpraesentation.pdf.
15. MERIT (Maastricht Economic and social Research and training centre on Innovation and
Technology) (2008). European Innovation Scoreboard 2008 – Comparative analysis of
innovation performance. Maastricht: MERIT. Retrieved from:
http://www.proinno-europe.eu/metrics.
16. Nilsson, P.I., Achtert, M., Grosseschmidt. H. (2010). Pathways to Innovation Excellence.
Results of a Global Study by Arthur D. Little.
17. Rüggeberg, H. (2008). Innovationsprozesse in kleinen und mittleren Unternehmen.
Working Papers of the Institute of Management Berlin. Paper No.41, 06/2008. Berlin:
Berlin School of Economics.
18. Scarlat, C. (1980). Metoda de stabilire a nivelului tehnic al produselor industriale
complexe / Method to assess the technical performance level of complex industrial
products. Proceedings of the First Symposium “Cybernetics Modeling of Operation
Processes”, May 1980. Bucharest: Academy for Economic Studies.
19. Scarlat, C. (1981). O abordare sistemică a problemei nivelului tehnic al produselor / A
systemic approach of the issue of the products’ performance level. Proceedings of the 2nd
Symposium “Cybernetics Modeling of Operation Processes”, April 1981. Bucharest:
Academy for Economic Studies Press.
20. Scarlat, C. (1987). Metoda distanţei tehnice (DISTEH). N. Stoica and C. Scarlat (Eds.):
Organizarea şi conducerea întreprinderilor / Enterprise organizing and leading, vol. I.
Bucharest: Polytechnic Institute Press. 274-298.
21. Scarlat, C. (2000). Metoda distanţei tehnice. O. Nicolescu (Ed.): Sisteme, metode şi tehnici
manageriale ale organizaţiei / Systems, methods, and techniques for organization
management. Bucharest: Ed. Economica. 369-378.
22. Scarlat, C. (2004). Innovative Technologies and Right Pricing Decisions in Marketing,
EBS Review: Innovation and Knowledge Sharing. Summer 2004, 18, 42-46. Tallinn:
Estonian Business School.
23. Scarlat, C. (2005a). Innovative Model for Innovative Technologies Analysis.
Nonconventional Technologies Review. 2, 75-82.
24. Scarlat, C. (2005b). Innovative Model for Product & Price Decisions in Marketing. C.
Chakraborty, C. Jayachandran, R. Misra (Eds.): Proceedings of The 9th International
Conference on Global Business and Economic Development “Management Challenges in
Times of Global Change and Uncertainty”, vol. III. Seoul: University Press. 1749-1756.
25. Scarlat, C. (2005c). The DISTEH Multicriteria Decision Making Model. Proceedings of
the Sixth International Conference on Operations & Quantitative Management (ICOQM-
6): “Intelligent Decision Making: Emerging Strategy for Global Winners”, August 9-11,
2005. Indore: Indian Institute of Management.
26. Scarlat, C. (2006). Models for Technology Prediction. Proceedings of the International
Conference on “Technology and Quality for Sustained Development – TQSD 2006”.
Bucharest: Academy of Technical Sciences of Romania, AGIR Publishing House. 541546.
27. Scarlat, C., Alexe, C.G. (2010). The influence of innovation on strategies of Romanian
service firms, International Journal of Innovation and Learning (IJIL). 8 (3), 267-278.
Retrieved from: www.inderscience.com/ijil.
28. Scarlat, C., Alexe, C.G., Alexe, C.M., Simion, C.P. (2010). Score-based assessment of the
innovation capability – at company level. Proceedings of the 2010 International
Conference on Technology Innovation and Industrial Management - TIIM 2010. 16-18
June, 2010, Pattaya, Thailand. S3 24-39.
29. Warschat, J. (2005). Der Weg zur Innovationsexzellenz. Stuttgart: Vorlesungsunterlagen
Universität Stuttgart, Institut für Arbeitswissenschaft und Technologiemanagement.
30. Wolfe, R. (1994). Organizational Innovation: Review, Critique and Suggested Research
Directions. Journal of Management Studies. 31, 405-431.
31. Wolpert, J. (2002). Breaking Out of the Innovation Box. Harvard Business Review. 80
(2), 77–83.