The critical analysis of scenario construction in the polish foresight initiatives.
Nazarko, Joanicjusz ; Kononiuk, Anna
Introduction
According to Giddens, one of the most important features of the
contemporary society is its attitude to time, particularly to the
future, which anticipation should be well-thought-of and in the ideal
situation carefully planned (Tsoukas, Shepherd 2004). This thesis seems
to gain its importance in times characterized by the high dynamics of
social, economic, technological, political and legal factors which
influence the processing of information coming from a great variety of
sources. As noted by Zavadskas and Turskis (2010), in many real-world
decision problems, a decision-maker has a set of multiple conflicting
objectives. Traditional forecasting methods-being fixed in their
assumptions-often fail to predict the future in turbulent times. A
policy tool that takes into perspective the widely understood
environment is foresight defined as systemic, participatory, future
intelligence gathering and medium to long term vision building process
aimed at present day decisions and mobilizing joint actions (Georghiou
et al. 2008). It should be emphasized that the complexity and essence of
foresight makes it not only a useful tool of future anticipation, but
also an element of its shaping and even managing. The uniqueness of
foresight is its additive value, which is a desired future vision. The
creation of desired visions is possible due to the implementation of the
scenario method in foresight research process. As noted by Bradfield et
al. (2005) scenarios may be treated as forums to involve multiple
agencies and stakeholders in policy decisions, enablingjoined-up
analysis and creating an accommodation platform to assist policy
implementation. Nevertheless, the majority of the existing published
works focuses on the adaptation of the scenario method to strategic
management in enterprises, taking no account of its meaning in foresight
studies funded by public institutions. (Gierszewska, Romanowska 2009;
Heijden 1996; Ringland 1998; Lindgren, Banhold 2003; Heijden et al.
2002; Perechuda, Sobinska 2008; O'Keefe, Wright 2010). To the
authors' knowledge, the problem of critical analysis of scenario
method construction in foresight studies has not been touched upon. The
aim of this article is to fill this knowledge gap.
1. The concept of scenario method
In the process of the scenario method's evolution, there have
been posited many definitions and possible approaches to and techniques
of scenario construction. Although the method is perceived as the basic
one of future studies, the notion of a scenario is increasingly misused
and abused (Godet, Roubelaut 1996) and as noted by Khakee gives rise to
confusion (Bradfield et al. 2005). The objective of this paper is to
begin to address this confusion by tracing the different methodologies
of scenario construction in the Polish foresight studies.
According to Ringland (1998) scenarios are the part of strategic
planning that relates to the tools and techniques of uncertainty
management. At the same time, Ringland emphasises that scenarios should
not be equal to forecast understood as the description of reality
projection or the vision, and indicates that forecast is only a single
picture of reality. Ringland's perception of the scenario method
seems to correspond with that of other futures scholars such as
Schwartz, van der Heidjen and Schutte (Van der Heidjen, Schutte 2000),
and Sarpong who state that the essence of the scenario method is not
knowing about the future, but rather preparing for it (Sarpong 2011).
The authors of this article also share this view.
Van der Heijden enlists five features of well written scenarios,
namely: linking historical and present events with hypothetical events
in the future, carrying storylines that can be expressed in simple
diagrams, plausibility, reflecting pre-determined elements, and
identifying signposts or indicators that a given story is occurring
(Saritas, Nugroho 2012).
For the benefit of foresight studies, the authors of this article
modify the definition of the scenario method proposed by Jasinski (1999)
who perceives scenario method as a description of logical and coherent
course of events with the aim of presenting how the current state of
reality transforms into a new one. A scenario is a description of
factors' interdependence determining the development of the given
situation in time. The interdependence between factors could be so
minutely described that the simulation of the given situation is
possible.
The authors posit the complementary to Jasinski's definition
of scenario method, perceiving it as the logical and formal construction
of an alternative vision of the desired future based on the involvement
of heterogeneous experts' groups taking into account the detailed
study and understanding of factors shaping researched phenomenon and
enabling the making of reasonable decisions about the future.
The emphasis on the heterogeneity of experts stems from the
authors' studies of minimum quality criteria for the scenarios
introduced by Stewart (2008). The first criterion concerns the change in
the perception of the world by the people involved in scenario
construction. This criterion seems to be parallel to Wack's
postulate, according to whom the most important aim of the scenario
method is challenging decision makers' assumptions about the
world's functioning, and at the same time convincing them to change
their perception of reality, which may even result in revolutionary
transformation.
The second criterion is based on Ashby's Law of Requisite
Variety and states that the scenario method is useful only when it is
based on the diversity of worldviews (Stewart 2008). The authors of the
article state that minimum quality criteria posited by Stewart seem to
be indispensable to understanding the scenario method, and therefore the
authors posit their application for foresight studies.
At the same time, the authors of the article posit that
heterogeneity of the experts may be enhanced by the triangulation
concept, which involves looking at the same phenomenon or research
question-from more than one source of data (Decrop 1999). It could also
be perceived as an assessment of the research phenomena form different
points of view with the aim of better understanding its variety (Stake
2009).
2. The evolution of scenario method
According to the authors of the article, in the last decade, the
development of the scenario method was significantly enhanced by the
publications of authors such as van Notten et al. (2003), Aligica
(2005), Bradfield et al. (2005), Borjeson et al. (2006), Hiltunen
(2006), Zurek and Heinrichs (2007), Bishop et al. (2007), Stewart
(2008), Saritas and Nugroho (2012) and van Vliet et al. (2012).
The works of van Notten et al. (2003) and Borjeson et al. (2006)
were devoted to the typology and classification of scenarios. Bradfield
et al. (2005) carried out comparative analysis of the three schools of
scenario construction, namely the school of intuitive logic that of
probabilistic modified trends school and La Prospective. The work of
Hiltunen (2006) primarily focused on the relation between weak signals,
cards and scenarios. Aligicia (2005) described the role of
epistemological element in scenario construction aiming at the
complexity and uncertainty reduction, knowledge increase and new
knowledge creation presenting at the same time-arguments for those
researchers who question the scientific character of the scenario
method. The work of Zurek and Heinrich (2007) is devoted to the
presentation of possible ways of linking scenarios across geographical
scales in international environmental assessment. The authors
differentiate between five ways of possible linking, namely: equivalent,
consistent, coherent, comparable and complementary. The aim of the work
of Bishop et al. (2007) was the presentation of possible scenario
techniques. The authors demonstrated the usefulness and strong and weak
sides of 23 techniques grouped into eight categories. The work of
Stewart (2008) is devoted to the presentation of the experience of
Australian futurologists on the new approach to scenario construction
based on integrated theories, especially Wilber's AQAL (All
Quandrant, All Level, All Lines, All States, All Types) metatheory.
Saritas and Nugroho (2012) combine systemic foresight, network analysis
and scenario methods to propose an 'Evolutionary Scenario
Approach', which explains the ways in which the future may unfold,
based on the mapping of the gradual change and the dynamics of aspects
or variables that characterise a series of circumstances in a period of
time. Results of the work by van Vliet et al. (2012) show that the use
of structuring tools can have a negative effect on the creativity of the
workshop, but the influence seems to vary between the different tools.
The problem of using scenarios for future anticipation is still present
in the leading journals on technological change (Cairns et al. 2013).
3. Polish foresight studies
Until 2012, in Poland more than forty national, regional and
sectoral foresight projects were carried out. The first steps of
foresight in Poland were taken in year 2003-2005 by the Ministry of
Science and Informatization, which carried out the Pilot Foresight
Program in the field of Health and Life. An important landmark in Polish
foresight history was the National Foresight Program "Poland
2020" (carried out from February 2006 to March 2009). To implement
project's results, the Ministry of Science and Higher Education
launched the third national foresight project entitled "National
Foresight Programme-the results' implementation".
Besides national projects, in Poland there have been taken the
following projects of sectoral, regional and thematic type, namely
(Kononiuk 2013):
--eighteen completed regional and sectoral foresight projects
granted financial support from the Sectoral Operational Programme
"Improvement of the Competitiveness of Enterprises" (Priority
1: "Enhancement of a knowledge-based economy and the business
environment", Measure 1.4: "Strengthening of co-operation
between the R&D sphere and the economy", Submeasure 1.4.5:
"Research and applied projects in the area of monitoring and
foresight of technology development";
--twenty two regional and sectoral foresight projects which were
granted the financial support from the EU Operational Program
"Innovative Economy 2007-2013" (Priority 1: "Research and
development of new technologies", Measure 1.1: "Support for
scientific research for the building of knowledge based economy",
Submeasure 1.1.1: "Research projects with the use of foresight
method";
--two thematic foresight projects, i.e. on human capital in modern
economy and technological foresight of Polish industry-Insight 2030 as
well as two regional foresight projects carried out in the West
Pomeranian and Lublin Voivodships.
The thematic area of the Polish foresight initiatives focuses on
the issue of setting the vision of development of both traditional
branches such as founding, copper, lignite, coal extraction industry,
and forestry, as well as the modern sectors such as metallic, ceramic
and composite materials, cosmic technologies, or nanotechnologies.
For the time being, the most updated state of the art of Polish
foresight studies may be found in the expertise commissioned by the
Ministry of Science and Higher Education entitled Evaluation research of
the Polish Foresight Projects, carried out by the researchers from the
Bialystok University of Technology (Nazarko 2012). Other existing
published works on Polish foresight projects mainly comprise interim and
final reports on projects' results as well as publications
presenting methods or research process applied in foresight initiatives
and attempts of evaluation of foresight activities. The publications
concerning methodological issues focus on demonstrating the research
procedures in foresight projects (Nazarko, Ejdys 2011), the role of the
scenario method in future anticipation (Kononiuk 2010), the role of
roadmapping process in foresight studies (Sacio-Szymanska et al. 2010),
the importance of unprecedented events (i.e. weak signals or wild cards)
in future management (Kononiuk 2009) and weak signals in risk management
(Magruk 2009), the innovative classification of foresight research
methods (Magruk 2011), the role of knowledge and technology mapping
(Gudanowska 2011) and the application of structural analysis for the
classification of factors influencing regional nanotechnology
development (Nazarko et al. 2011) to name but a few. The attempts of
evaluation concern foresight projects of all types. The assessment of
the Polish National Foresight Program "Poland 2020" may be
found in publications of the Ministry of Science and Higher Education
(Ministry of Science and Higher Education 2009), the publications of the
Forecasts Committee "Poland 2000 PLUS" (Kleer, Wierzbicki
2009), the expertise of Central Mining Institute (Central Mining
Institute 2007) and publications on the role of Delphi method in the
National Foresight Program "Poland 2020" (Kowalewska,
Gluszczynski 2009) and the role of the Support Group comprising young
scientists in the same foresight exercise (Kononiuk et al. 2009). The
evaluation of regional and sectoral foresight initiatives may be found
in publications by Glinska et al. (2008), Rogut and Piasecki (2011),
Nazarko (2012), Nazarko et al. (2013).
4. The critical analysis of scenario construction in Polish
foresight regional and sectoral initiatives
The source of data for the critical analysis of scenario
construction in Polish foresight regional and sectoral initiatives are:
questionnaires addressed to sectoral foresight project coordinators; the
unpublished PhD thesis by Kononiuk (2010) on scenario method application
in foresight studies; content analysis of projects' final and
interim reports as well as projects' web pages.
Research for this paper has been carried out in three phases. The
first phase was the identification of all completed foresight projects,
in which the scenario method has been applied. The source of data for
this phase was the PhD thesis by Kononiuk. The authors have identified
eighteen foresight projects which were granted the financial support
from the Sectoral Operational Programme "Improvement of the
Competitiveness of Enterprises" (Priority 1: "Enhancement of a
knowledge-based economy and the business environment", Measure 1.4:
"Strengthening of co-operation between the R&D sphere and the
economy", Submeasure 1.4.5: "Research and applied projects in
the area of monitoring and foresight of technology development").
The second phase was the collection of data from the projects'
coordinators through questionnaires. The aim of the third part was to
derive the missing data, which was done on the basis of content analysis
of projects' final and interim reports as well as projects'
web pages.
The names of foresight projects of regional and sectoral type have
been presented in Tables 1 and 2.
The questionnaires were completed by seventeen of eighteen
respondents. The respondents of MEDT project refused to take part in the
research. Nevertheless, the authors of the article gained the
information about their method of scenario construction on the basis of
final report (Wojcicki, Eadyzynski 2008).
For the purpose of this publication, the authors would like to
present projects' coordinators' answers to the following
research questions:
1. What approach has been used to scenario construction?
2. What are the most important phases of scenario construction?
3. What is the interconnection of scenario method with other
methods of scenario construction?
4. What is the profile of experts involved in foresight projects?
5. What is the profile of experts involved in scenario
construction?
6. Has the selection of experts been supported by triangulation?
7. Have the wild cards been taken into account? What kind of
technique has been applied in the process of their identification?
8. What is the average time of scenario construction process?
9. Is there a linkage of scenarios to other documents?
10. How many scenarios have been elaborated?
11. What are the main difficulties in the process of scenario
construction?
4.1. Adopted approach
The first research problem concerned the approach applied to
scenario construction. In particular, the authors of the study were
interested in whether or not the scenario construction processes in
Polish regional and sectoral foresight initiatives were supported by
experts working in panels, cross-impact analysis, or morphological
analysis. The aforementioned three approaches have been described by
Ringland (1998). On the basis of completed questionnaire analysis in all
cases, expert approach was used. Executors of projects such as FEI, PV,
MCCM, MAV, PM, CE, SLV reported that they had additionally used
cross-impact analysis.
4.2. The key phases of scenario construction and the
interconnection of scenario method with other methods
The key issue of the authors' interest was getting to know the
way of scenario construction in projects under analysis. On the basis of
answers analysis, it may be concluded that the process of scenario
construction within projects varies significantly. The key phases of
scenario construction indicated by respondents are presented in Table 3.
Scenario building phases have been distinguished in sixteen out of
seventeen analysed cases, that is, with the exclusion of SWV
respondents. The analysis of the data on scenario building phases in
Table 3 shows that the data has been presented at different levels of
detail. In some cases, phase descriptions seemed to be limited to
scenario building methods, i.e. in PF, AV, PKV and DSV with the
respondents claiming that the scenarios had been built in the scope of
workshops (AV, PKV, DSV) or by trade consultations (PF). In other cases,
scenario building phases have been presented at a high degree of
generality (OPV) and constituted project methodology characterization
rather than the actual scenario building phases (RM, MPV, LOV). In PM,
SLV, FEI, the respondents described actions taken after scenario
building, that is: marking out the environment behaviour variants,
formulating a technological development vision, and determining the
probability of the vision coming to life for given variants. In two
cases, i.e. SWZ and MZV, the respondents were unable to name scenario
building phases. More detailed scenario building phases were only
indicated by LE, CE, SCT and MCCM respondents.
That being so, the authors have asked the respondents to send
detailed reports on scenario building work in individual projects or
publications on the subject matter from projects of that type. Source
materials were obtained from fifteen out of eighteen analyzed projects,
with the exclusion of PF, PM and LE.
On the basis of the scenario building phases analysis, four
prominent scenario building forms can be distinguished: optimization
modeling, scenario building based on key factors' behavior
description, scenario building based on Delphi method results, and
scenario building based on scenario workshops results.
LE and CE executors have applied optimization modeling. In LE,
scenario building came down to simulation modeling. By contrast,
scenario building in CE was based on (Dubinski, Turek 2008):
--a current state diagnosis in the scope of hard bituminous coal
technology, collecting statistical data in the quantitative form;
--an introduction of trend-describing data choice algorithm, its
extrapolation for developed future visions;
--formulating a list of possible future events which will influence
trend lines;
--a correction of trend lines made on the basis of
expert-identified event occurrence probability assessment.
A scenario structure based on key factors analysis has been applied
in SCT, OPV, MCCM, PM, FEI, SLV and MEDT. At the same time, in SCT,
relations among factors were not determined and the execution of the
scenario method came down to building three possible scenarios of space
activity financing in Poland. The work resulted in Scenario
"Zero", Scenario "Poland as a member of ESA" and
Scenario "Poland as a member of ESA with a complimentary national
programme". In OPV project, scenario building was achieved through
identification of causative success factors for each research area, and
its result was the building of an optimistic, a pessimistic and a
business-as-usual scenario for chemistry trade. The attempt to determine
relations among factors in chosen research areas was made in MCCM, PM,
FEI, SLV and MEDT. The most formalized scenario building process,
complemented by the implementation of key technologies and the results
of the Delphi survey, can be distinguished in PM, FEI and SLV executed
in cooperation with Central Mining Institute in Katowice. The process
has been presented in Figure 1.
[FIGURE 1 OMITTED]
The presented diagram illustrates the fact that three elements had
direct influence on the scenario building, i.e. foreseeing variants of
future environment behavior, a list of key technologies, and Delphi
survey results. Furthermore, in Figure 1 the relation between key
factors and Delphi survey has been marked, with the relation being
highlighted in SLV. The authors obtained the scenarios in their final
forms from FEI and SLV. The scenario method results were constituted by
building of an optimistic, a realistic and a pessimistic scenario for
FEI (Czaplicka-Kolarz 2007) and an optimistic, a realistic, a stagnation
and a pessimistic scenario for SLV in the scope of defined research
areas. Key factors in the aforementioned scenarios were distinguished on
the grounds of their mutual relations analysis with the use of the
MIC-MAC computer programme. In the case of PM, the respondents refused
to present detailed reports on the course of scenario building.
Methodology similar to the one used in PM, SLV and FEI was used in MEDT
as well. Seven following phases can be discerned in that methodology
(Wojcicki, Ladyzyski, 2008):
1. Identification of success and uncertainty factors which
determine the future of medical technologies sector in Poland by 2020
based on SWOT analysis results and considering current sector condition
analysis results as well as STEEP analysis.
2. Establishing main scenario topics on the basis of assumed
behaviour on the part of factor pairs, which have the most significant
influence on technology success and the greatest uncertainty in three
condition categories: socio-economic, scientific-technological and
business.
3. Consolidation of corresponding success and uncertainty factors
in all three condition categories, leading to four sets of collective
scenario assumptions.
4. Establishing the behaviour of key variables distinguished in
cross-impact analysis in a way that allows for assumptions on individual
scenarios to be fulfilled, and therefore enabling prerequisites of their
execution to be realized.
5. Building four scenarios in a descriptive form (including two
variants of a random scenario).
6. Forming a future vision of key technologies for each of the
built scenarios, in each panel's subject area and its
generalization for the whole medical technologies field.
7. Instituting technological implementation areas in industry,
medicine and health service.
The Delphi survey had a direct influence on scenario building in
LOV, MPV (Hausner 2008), RM (Drzewiecki et al. 2008) and MZV (Szewczyk
2008). While analysing research reports, the authors have noted that in
those studies, the product of scenario method was highlighted more than
the implementation mechanism of the Delphi method results into the
scenarios. In LOV, success scenarios method was used which consisted in
choosing the scenario leading to the voivodeship's sustainable
development among alternatives of the voivodeship's future
development. As a result of LOV project work, Development scenarios of a
voivodeship as a knowledge-based region and Scenarios of regional
industries transformation have been created (Rogut, Piasecki 2008). On
the other hand, as a result of a Delphi survey used in CO scenario, the
following scenarios were discerned: a moderate and a sustainable
development scenario, an accelerated development scenario, and-the most
costly, but also highly expected-dynamic development scenario
(Drzewiecki et al. 2008). The outcome of MPV project work was generating
an optimistic scenario, a pessimistic scenario and a business-as-usual
scenario for the following research areas: economic growth,
infrastructure, natural resources and new materials (Hausner 2008). The
effect of MZV project work was building neutral, negative and positive
scenarios (Szewczyk 2008). In those scenarios the following elements
were distinguished: economic growth, infrastructure development and
spatial development, human capital, science development, political
circumstances, sociological changes and changes in the natural
environment (Szewczyk 2008).
Scenario building on the basis of workshops and panel discussions
can be observed in four projects: PF, DSV, PKV and OPV. Attributing a
key role to discussion panels in scenario building, with the exception
of PF and DSV (see Table 3), can also be noted in PKV and AV. In PKV,
the scenario was built through an environment factors analysis and
integration of fictional factors (devised by teams of two experts) with
the most probable, optimistic and pessimistic scenarios (Methodology of
work execution in Priority Technologies for Sustainable Development of
the Podkarpackie Voivodship project, no pagination. (Source material
sent by PKV respondents). In a detailed analysis of AV project work, the
authors have noticed that the final scenario formulated within the
project that is Aviation industry development scenario amounted to one
scenario of foresighted environment changes and was preceded by three
scenarios, i.e. Scenarios: possible directions of development strategy
for research and development infrastructure. The detailed scenarios
built within AV are the following (Material Technologies Development
Directions for "Dolina Lotnicza" Aviation Cluster. Sector
foresight. Project execution final report):
--Organizing a team of research laboratories working for aviation
industry.
--Research and development based on the best and geographically
closest academic-research units.
--Research centers working for individual companies' centers
of excellence.
The scenarios put forward have been developed without explicit
probability degrees; instead, they constituted visions, in which
advantages and disadvantages were distinguished.
Based on the analysis of scenario building forms in Polish regional
and trade foresight projects, the article authors have attempted to
determine the extent to which the presented scenario building forms
correspond to foresight research nature. Scenario building derived from
optimization modeling harmonizes with the concept of probabilistic trend
modification school, which, in spite of many strong points manifested in
the option of assistance of mathematical probabilistic computer models
and generating alternative future visions in the form of scenarios which
are developed as a result of fusing assumed future events with expert
assessment (Dubinski, Turek 2008) hampers broad social participation and
interaction, which is a foresight research principle. The three
remaining leading scenario building forms seem to correlate better to
foresight research principles, mainly because of distinguishing the
so-called key factors, engaging a wide circle of experts owing to the
Delphi method and proposing interactions within scenario workshops. In
the article authors' opinion, scenario building in MCCM, PM, FEI,
SLV and MEDT were the closest to the intuitive logic school concept due
to key factors defining and establishing their mutual relations.
Nevertheless, the authors have noted that the final forms of scenarios
are optimistic, pessimistic and neutral, which-according to
practitioners in the field of scenario method in foresight research such
as Miles, Ringland and Ravetz (2007)-can encourage governing bodies to
choose a business-as-usual variant, the neutral one, and thus
substantially reduce the significance of constructed alternative future
state concepts. Exceptions to this tendency were only the scenarios
within LOV and AV.
4.3. Expert structure in foresight projects
Even more important than the number of experts engaged in the
project seems the expert structure that indicates a consensus among many
social groups when it comes to future visions. On account of that, the
authors of this publication have questioned the respondents about the
structure of the experts engaged in the project and the scenario
building. By the structure of experts the authors mean the number of
academics, businesspeople, politicians and civil servants, media
members, non-governmental organizations, students actively committed to
project work. Eight out of seventeen executors of analysed projects were
able to provide a detailed expert structure at the project level, namely
DSV, CO, PF, OPV, SLV, MCCM, AV and SWV. The structure is presented in
Figure 2.
On the basis of the data depicted in Figure 2 it can be noted that
the most diverse expert structure was applied in three projects, DS,
MCCM and SWV. In the case of DSV and MCCM, four expert groups were on
the expert teams: academics, businesspeople, politicians and civil
servants, who accounted for 55%, 18%, 18% and 9% respectively in DSV and
84.5%, 9.5%, 3% and 2% in MCCM. The structure of SWV was based on expert
groups different than in DSV and MCCM; to be exact, apart from
academics, businesspeople, politicians and civil servants, amounting to
48%, 28% and 20% respectively, there was also "other" category
amounting to 4%. In OPV and SLV the respondents named three expert
groups, i.e. academics, businesspeople, politicians and civil servants,
who constituted 55.5%, 20% and 24.5% respectively in OPV and 14%, 72%
and 14% in SLV. In AV, there were also three groups on the expert team;
apart from academics and businesspeople, non-governmental organizations
were invited. These groups' shares in the expert team reached 49%,
49% and 2% respectively. In the remaining two projects, the respondents
named only two expert groups, that is academics and businesspeople, who
constituted 65% and 35% respectively of the expert team in CO and 80%
and 20% in PF. In six out of eight analysed cases, i.e. in DSV, CO, PF,
OPV, MCCM and SWV, definitely the most numerous group was academics,
whose share equaled from 55% for DS to 84.5% for MCCM. An exception to
this tendency was the expert structure in SLV, where clearly the largest
group was businesspeople at 72%; the percentage of other expert groups,
namely academics and non-governmental organizations with civil servants,
amounted to 14% for both of the above groups. In the remaining projects,
PM, LOV, FEI and MPV, academics vastly outnumbered other expert groups.
The respondents from SCT, MZV, LE and CE were unable to present an
expert structure. However, in the case of SCT, three expert groups were
declared (academics, businesspeople and politicians with civil servants)
and in the case of CE, the respondents claimed that "many expert
groups" partook in the research.
4.4. The profile of experts involved in scenario construction
The results presented in the previous subsection that concern the
structure of experts involved in analysed foresight projects suggest
that the reached consensus on development visions for the researched
areas is quite often not based on agreement among many social groups.
The situation is similar when it comes to experts participating in the
scenario method whose point-according to foresight research idea-is to
formulate desired development visions devised by many stakeholders. The
expert team structure engaged in building scenarios was presented by
respondents from only six projects: PF, MCCM, AV, CO, OPV and SWV. The
structure has been presented in Figure 3.
The most diverse structure of experts involved in scenario building
was a feature of MCCM and SWV, whose expert teams each consisted of four
expert groups. In MCCM, the expert structure was made of academics,
businesspeople, civil servants and media members, whose share in the
expert structure accounted for 71%, 12%, 12% and 5% respectively. The
expert groups responsible for scenario building in SWV consisted of
academics, businesspeople, politicians with civil servants and experts
from the "other" category. The percentages of the groups
mentioned above in the expert structure were 48%, 28%, 20% and 4%
respectively.
Representatives of three circles were engaged in scenario building
within CO and OPV, namely: academics, mining industry representatives
and mining bureau representatives at 70%, 25% and 5% respectively in CO
and academics, businesspeople, politicians and civil servants at 43%,
26% and 31% in OPV. Three expert groups participating in scenario
development can be also identified in AV: academics, businesspeople and
non-governmental organizations at 50%, 47% and 3%.
In PF only two expert groups have been recognized: academics, whose
share was 90% and industry representatives, who made up 10% of the team.
On the grounds of these facts, the authors question the consensus among
many social groups on future visions which, after all, should be the
paradigm of such type of research. In spite of the obstacles presented
above in defining the scenario method expert structure observed in most
researched foresight initiatives, sixteen out of seventeen project
executors declared that the choice of experts for the scenario method
was intentional. Only CO project executors gave a negative answer to the
question about choice intentionality.
4.5. The application of triangulation principle in scenario
construction
The questions about the structure of experts working on the project
and within the scenario method, and the question about the
intentionality of expert choice, as intended by the authors, were at the
same time test questions about utilizing the triangulation principle
(1). The authors have assumed that if there is little variety in the
expert structure or distinct dominance of one expert group, the
triangulation principle is most likely not applied. Meanwhile, the
results of triangulation principle application stand in contrast to the
authors' assumptions. The application of the triangulation
principle was declared by the executors of thirteen projects: MCCM, PM,
SLV, LE, PF, FEI, MPV, OPV, SWV, AV and CE claimed to have applied three
triangulation rules, namely the data triangulation rule, the
investigator triangulation rule and the theoretical triangulation rule.
The executors of DS asserted to have applied the investigator
triangulation rule and the theoretical triangulation partially; the
executors of PKV claimed to have applied the theoretical triangulation
rule; the executors of SCT declared the application of the investigator
triangulation rule. The executors of MZV and CO gave a negative answer
to the question about the application of the triangulation principle,
while LO executors did not answer this question. The results of the
research on the triangulation principle application seem to stand in
contrast to the results of the research on the expert structure. In the
authors' opinion, the executors' having applied all three
triangulation rules is questionable, especially in the cases where the
respondents were unable to name expert structures, i.e. in LE and CE; or
in the situation where the expert structure was not very diverse, i.e.
in PF, OPV and MCCM; or when there was significant dominance of one
expert group, namely academics, seen in the majority of researched
projects, i.e. DSV, CO, PF, OPV, MCCM, PM, LOV, FEI and MPV, or
businesspeople in SLV.
4.6. The application of wild cards into scenario construction and
techniques of their identification
The next issue that intrigued the article's authors was the
fact that the executors of the regional and sector foresight projects
considered unprecedented events in scenario building. Those events-of
high impact and low probability of occurrence-allow for alternative
future conditions to be considered, broadening the extent of occurrence
perception. Employing unprecedented events in scenario building in
Polish regional and sector foresight projects was dealt with in seven
initiatives: MZV, MCCM, FEI, CE, PM, PKV, and SCT. Based on
questionnaire analysis and telephone in-depth interviews conducted with
the executors of MZV and CE, the authors have established that the
unprecedented events were identified with the use of the brainstorming
technique. Specific unprecedented events were reported by two executors,
namely MZV and CE. In the case of MZV, the 2012 UEFA European Football
Championship, commonly referred to as Euro 2012, was recognized as an
unprecedented event, while in CE it was discussed whether it is feasible
to develop an effective energy production technology in the process of
controlled thermonuclear fusion. In the remaining instances, the authors
of the article were unable to obtain information on discussed
unprecedented events. This failure might be explained by certain
confidentiality of the research. On the other hand, refraining from
analysing unprecedented events might result from the lack of widely
available analysis tools or from unfamiliarity of relations between
unprecedented events and scenario building stages.
4.7. The average time of scenario construction process
The authors of the article have also enquired about the amount of
time Polish regional and sector foresight projects executors devote to
scenario building. The results have been collated in Figure 4.
The amount of time devoted to scenario method employment was
declared by sixteen out of seventeen respondents. The figure above does
not include data on total scenario building time in DSV and AV. For DSV,
this fact results from ambiguity in determining the total scenario
building time by the respondents; the answers offered were "from
three months up to two years". For AV, the total scenario building
time was estimated at a hundred hours, which is difficult to express on
a monthly scale. Meanwhile, SWV respondents were incapable of reporting
the total scenario building time. In Figure 4, one can see that the most
time was devoted to scenario building within LE, namely 25 months. Also
CE, CO and SLV had a long scenario building time, amounting to 16, 11
and 7 months respectively. In the remaining projects, the scenario
building time did not surpass six months each; the shortest time devoted
to scenario building was a feature of SCT and PKV. The data presented in
Figure 4 indicates that scenario building times are generally shorter
than in corresponding research worldwide (according to Miles et al.
2007), the average time dedicated to foresight research scenario
building equalling six months. The situation described above might be
the outcome of ascribing a lesser importance to the scenario method in
creating a vision of a researched area.
4.8. The linkage of scenarios to other documents
The authors' next goal was to examine whether the scenario
method in Polish regional and sector foresight projects is applied
solely on the basis of expert knowledge generated during project
execution, or the scenario method can be linked to other documents which
contain scenarios or documents of strategic nature.
In thirteen out of seventeen analysed cases there were references
to other documents. Specific documents were revealed by several
respondents, namely CE, PF, CO, FEI, LE and MCCM. In the majority of
analysed projects, apart from MCCM, experts referred to documents
directly linked to the researched area. The largest amount of documents
of that type was reported by CE respondents, who, among others,
mentioned the following documents:
1. Scenarios of Fuel-Energy Complex Technologies Development for
the Country's Energy Safety Guarantee;
2. The Strategy for Hard Bituminous Coal Mining in Poland
2007-2015;
3. Policy on Polish Power by 2030;
4. National Strategic Reference Framework 2007-2013 with
Operational Programmes;
5. Regional Operational Programme for the Slqskie Voivodship
2007-2013.
In other cases, respondents reported documents such as: Scenarios
for German founding (PF), Mining Industry of the Future, USA 2002,
Developement of the Minerals Cycle and the Need for Minerals, UK 2001
(CO), Policy on Polish Power by 2025, National Development Plan
2007-2013 (FEI). In LE, the respondents did not mention specific
documents; they only indicated that they referred to previous concepts
for prospective deposit development. MCCM executors consulted other
foresight projects executed in Poland and abroad, while in the scope of
DSV, reputable prognoses (Japanese, American and European ones) were
taken into account as far as scientific and technological development,
and innovative strategies for chosen UE regions were concerned. Two
projects that did not refer to other documents were PKV and AV. In PKV,
it was assumed that it would be executed on the grounds of information
gathered during its execution, so answers are not suggested. The
objective of the main expert panel in that project was to select
generated content and to evaluate it for the sake of creating the final
report. In the case of AV, the executors did not disclose the reasons
for not having referred to other documents. In the cases of LOV and SWV,
the author of the article did not manage to obtain answers as to a lack
of referral to other documents.
4.9. The number of built scenarios
The next issue which interested the authors of the article was the
number of built scenarios. In keeping with the concept of intuitive
logic, the optimal number of developed scenarios for foresight research
is two to four. Moreover, such a concept has been promoted by Miles et
al. (2007) who at the same time stress that a large number of built
scenarios hinders the perception of generated alternatives, can lead to
cognitive dissonance and thus become useless for potential
decision-makers. Therefore, the authors of the article deemed it
legitimate to attempt at identifying the number of scenarios built in
the researched Polish regional and sector foresight projects. The
outcomes are shown in Figure 5.
The data presented in Figure 5 demonstrates that the largest
amounts of scenarios were developed in PM and CE, where in total 56 and
36 scenarios, respectively, were created. Many scenarios were also built
in SLV, DSV, FEI, MPV, MCCM and MZV, ranging from 21 in SLV to 6 in OPV.
The postulate of the intuitive logic school about the number of
scenarios was only obeyed by the executors of PF, SCT, AV, CO, LOV and
PKV. The authors of the article were unable to obtain information about
the number of scenarios built within SWV. High numbers of built
scenarios can be explained by applying optimization modelling in LE and
CE, while a substantial number of built scenarios in SLV, DSV, FEI, MPV,
MCCM and MZV may result from the ineptitude at scenario integration, for
example to four alternatives of the researched region development, in
keeping with the scenario building postulate of intuitive logic school.
4.10. Difficulties in scenario building
Finally, the authors have asked the respondents to name
difficulties in scenario building in order to identify any problem areas
in applying the method. The difficulties were expressed by nine
respondents and were of different types, i.e. some problems concerned
the availability of initial statistical data required for scenario
building as well as relations between the scenario method and the scope
of research areas, while others dealt with the approach to scenario
building, outcome popularization or technical aspects. The most
frequently encountered difficulty was the lack of statistical data from
the scope of the research. The problem was reported by respondents DSV,
MPV and CE. Other difficulties included "too broadly defined
research areas" that brought about building mutually exclusive
scenarios (FEI), working out cohesive scenarios for several research
areas (MZV), different approaches to scenario building in each panel
(PKV) and internalization of foresight results by the authorities and
region's decision-makers (OPV). For CO respondents, the crucial
difficulty was changeable boundary conditions, i.e. mainly prices of
copper and accompanying metals. The PM respondents reported a problem
caused by substantial diversity in expert numbers, work quality, the
scope of research and timeliness of result delivery.
Conclusions
The critical analysis of the employment of the scenario method in
Polish regional and sector foresight projects presented in this article
has allowed for the diagnosis to be established on using the method in
the Polish context. The authors have obtained answers to research
problems through questionnaire analysis. The expert approach was widely
used to scenario building in the analysed projects, although respondents
from several projects reported using cross-impact analysis. The analyses
of questionnaire data and of detailed reports on project execution
methodology led to the identification of four leading scenario building
forms, namely optimization modelling, scenario building based on
description of key factors, as well as on the results of the Delphi
method and the scenario workshop. The data on the structures of experts
engaged in the projects and in the scenario method indicates that the
achieved consensus on development visions for the researched areas in
many cases is not based on a consensus among many social groups.
However, despite the lack of explicitness in defining expert structures
in the scenario method detected in the majority of researched foresight
initiatives, most project executors declared that the choice of experts
for the scenario method was intentional. Also, employing the
triangulation method for the sake of expert choice raises many doubts;
although declared by the majority of the respondents, it stands in
opposition to the results of expert structures analysis. The presented
analysis has allowed for identification of projects in which
unprecedented events were utilized; in some cases, establishing their
identification technique, namely brainstorming in accordance with STEEP
analysis criteria; and distinguishing rare examples of unprecedented
events in the Polish context. However, using unprecedented events in the
presented foresight initiatives should be deemed marginal, unstructured,
and thus unsatisfying. Moreover, the demonstrated research results imply
that in most cases less time is devoted to scenario building than in
research of this type worldwide, where the average scenario-building
time is six months. Despite the declarations on the expert approach to
scenario building, in most cases, project executors also make use of
other documents to build scenarios. The results presented in this
subsection helped to establish problem areas of applying this method in
the Polish context. Among the difficulties, the respondents named, for
example, difficult access to statistical data essential for scenario
building, research areas defined in an ambiguous way, or problems
related to scenario integration. The comments above let the authors
diagnose the application of the scenario method in foresight
initiatives, and allowed them to identify the critical problems of its
usage.
Caption: Fig. 1. Scenario building process in PM, SLV and FEI
projects Source: Authors' own study on the basis of among others
Czaplicka-Kolarz (2007).
doi:10.3846/20294913.2013.809030
References
Aligica, P. D. 2005. Scenarios and the growth of knowledge: notes
on the epistemic element in scenario building, Technological Forecasting
and Social Change 72(7): 815-824.
http://dx.doi.org/10.1016rj.techfore.2005.01.001
Bishop, P.; Hines, A.; Collins, T. 2007. The current state of
scenario development: an overview of techniques, Foresight 9(1): 5-25.
http://dx.doi.org/10.1108/14636680710727516
Borjeson, L.; Hojer, M.; Dreborg, K-H.; Ekvall, T.; Finnveden, G.;
2006. Scenario types and techniques: towards a user's guide,
Futures 38(7): 723-739. http://dx.doi.org/10.1016/j.futures.2005.12.002
Bradfield, R.; Wright, G.; Burt, G.; Cairns, G.; van der Heijden,
K. 2005. The origins and evolution of scenario techniques in long range
business planning, Futures 37(8): 795-812.
http://dx.doi.org/10.1016/j.futures.2005.01.003
Cairns, G.; Ahmed, I.; Mullet, J.; Wright, G. 2013. Scenario method
and stakeholder engagement: critical reflections on acclimate change
scenarios case study, Technological Forecasting and Social Change 80:
1-10. http://dx.doi.org/10.1016/j.techfore.2012.08.005
Czaplicka-Kolarz, K. (Ed.). 2007. Scenariusze rozwoju
technologicznego kompleksupaliwowo-energetycznego dla zapewnienia
bezpieczeustwa energetycznego kraju, Cz. 2 [Scenarios of fuel-energy
complex technologies development for the country's energy safety
guarantee. Part 2]. Katowice, Glowny Instytut Gornictwa [Central Mining
Institute].
Central Mining Institute 2007. Analiza tematyki projektow typu
foresightprowadzonych w Polsce i ocena spojnosci ich planowanych wynikow
z zamierzeniami Narodowego Projektu Foresight "Polska 2020"
[The analysis of the thematic areas of Polish foresight projects and the
assessment of its correspondence to the Polish National Foresight
Programme "Poland 2020"], ekspertyza Glownego Instytutu
Gornictwa, Katowice.
Decrop, A. 1999. Triangulation in qualitative tourism research,
Tourism Management 20: 157-161.
http://dx.doi.org/10.1016/S0261-5177(98)00102-2
Drzewiecki, J.; Butra, J.; Kosior, A. 2008. Scenariusze rozwoju
technologicznego przemyslu wydobywczego rud miedzi i surowcow
towarzyszacych w Polsce [Technological development scenarios for copper
and accompanying metals mining industry in Poland], Cuprum 1(46):
185-204.
Dubinski, J.; Turek, M. 2008. Sposob tworzenia scenariuszy rozwoju
technologicznego przemyslu wydobywczego wcgla kamiennego [Scenario
building for hard bituminous coal mining technological development],
Gospodarka surowcami mineralnymi 24(1/2): 13-30.
Georghiou, L.; Cassingea Harper, J.; Keenan, M.; Miles, I.; Popper,
R. 2008. The handbook of technology foresight. Concepts and practice,
Prime Series on Research and Innovation Policy, Northampton: Edward
Elgar Publishing, Inc.
Gierszewska, G.; Romanowska, M. 2009. Analiza strategiczna
przedsicbiorstwa. Warszawa: PWE.
Glinska, U.; Kononiuk, A.; Nazarko, t. 2008. Przeglad projektow
foresightu branzowego w Polsce [A review of sector foresight projects in
Poland], Nauka i Szkolnictwo Wyzsze [Science and Higher Education]
2(32): 60-73.
Godet, M.; Roubelat, F. 1996. Creating the future: the use and
misuse of scenarios, Long Range Planning 29(2):164-171.
http://dx.doi.org/10.1016/0024-6301(96)00004-0
Gudanowska, A. 2011. Mapy wiedzy jako narzedzie lokalizacji zasobow
wiedzy w organizacji [Knowledge maps as a localization tool of knowledge
resources in organization], Problemy Eksploatacji [Mainetance Problems]
3: 19-31.
Hausner, J. (Ed.). 2008. Foresight technologiczny na rzecz
zrownowazonego rozwoju Malopolski [Technological Foresight for
Sustainable Development of Malopolska], [online]. Krakow: Malopolska
Szkola Administracji Publicznej at Uniwersytet Ekonomiczny in Krakow,
[cited 9 December 2009]. Available from the Internet:
http://www.foresight.msap.pl/index.php?page=raports.
Heijden, K. 1996. Scenarios-the art of strategic conversation.
London: Wiley.
Heijden, K.; Bradfield, R.; Burt, G.; Cairns, G.; Wright, G. 2002.
The sixth sense: accelerating organizational learning with scenarios.
Chichester: Wiley.
Hiltunen, E. 2006. Was it a wild card or just our blindness to
gradual change?, Journal of Futures Studies 11(2): 61-74.
Jasinski, A. H. 1999. Metodyka badan rynku [The methodology of
market research]. Bialystok: Wydawnictwo Uniwersytetu w Bialymstoku.
Kleer, J.; Wierzbicki, A. 2009. Narodowy program foresight Polska
2020: Dyskusja zalozen scenariuszy [Polish national foresight programme
"Poland 2020": The diccusssion of scenarios assumptions],
Warszawa: Polska Akademia Nauk. Komitet Prognoz, 'Polska 2000
Plus'.
Kononiuk, A. 2009. Sposoby identyfikacji zdarzen bezprecedensowych
jako remedium na unikniecie badz lagodzenie skutkow potencjalnego
kryzysu [Ways of identifying unprecedented events as a remedy for
avoiding or moderating of effects of potential crisis], Prace i
Materiaty Wydziatu Zarzadzania Uniwersytetu Gdanskiego [Works and
Materials of the Faculty of Management at the University of Gdansk]
3(2): 527-537.
Kononiuk, A. 2010. Metoda scenariuszowa w antycypowaniu przyszlosci
(na przyktadzie Narodowego Programu Foresight "Polska 2020"),
Warszawa [Scenario analysis in future anticipation (in the light of the
"Polish National Foresight Programme 2020"], unpublished PhD
thesis, Warsaw University, Warsaw.
Kononiuk, A. 2013. Foresight jako nurt badawczy w naukach o
zarzadzaniu [Foresight as a research trend in management sciences],
Wspolczesne Zarzadzanie, forthcoming.
Kononiuk, A.; Magruk, A.; Nazarko, L. 2009. The concept of support
group in the Polish National Foresight Programme "Poland
2020", in Matwiejczuk, W. (Ed.). Zarzadzanie organizacja w nowej
rzeczywistosci gospodarczej: wybrane problem. Diffin, Warszawa.
Kowalewska, A.; Gluszczynski, I. 2009. Rola metody delfickiej w
Narodowym Programie Foresight "Polska 2020" [The role of
Delphi method in the Polish National Foresight Program "Poland
2020"]. Warszawa: Pentor Research International.
Lindgren, M.; Banhold, H. 2003. Scenario planning, the link between
future and strategy. New York: Palgrave Macmillan.
Magruk, A. 2009. 'Weak signals' w procesie zarzadzania
kryzysowego [Weak signals in the process of crisis management], Prace i
Materiaty Wydziatu Zarzqdzania Uniwersytetu Gdanskiego 3(2): 517-526.
Magruk, A. 2011. Innovative classification of technology foresight
methods, Technological and Economic Development of Economy 17(4):
700-715. http://dx.doi.org/10.3846/20294913.2011.649912
Miles, I.; Ravetz, J.; Ringland, G. 2007. A specialised course on
scenario building, UNIDO, 5-8 November, Prague.
Ministerstwo Nauki i Szkolnictwa Wyzszego [Ministry of Science and
Higher Education]. 2009. Wyniki Narodowego Programu Foresight
"Polska 2020" [The results of the Polish National Foresight
Programme "Poland 2020"]. Warszawa.
Nazarko, J.; Ejdys, J. (Eds.). 2011. Metodologia iprocedury
badawcze wprojekcie Foresight Technologiczny NT for Podlaskie2020:
Regionalna strategia rozwoju nanotechnologii [Methodology and Research
Procedures in Technology foresight "NT FOR Podlaskie 2020".
Regional strategy of nanotechnology development]. Oficyna Wydawnicza
Politechniki Bialostockiej, Bialystok.
Nazarko, J.; Wnorowski, H.; Kononiuk, A. (Eds.). 2011. Analiza
strukturalna czynnikow rozwoju nanotechnologii w wojewodztwie podlaskim
[Structural analysis of nanotechnology development factors in Podlaskie
Voivodship]. Bialystok: Oficyna Wydawnicza Politechniki Bialostockiej.
Nazarko, J. (Ed.). 2012. Badanie ewaluacyjne realizowanych w Polsce
projektow foresight [Evaluation research of the Polish foresight
projects]. Warszawa: Ministerstwo Nauki i Szkolnictwa Wyzszego.
Nazarko, J; Glinska, U.; Kononiuk, A; Nazarko, t. 2013. Sectoral
foresight in Poland: thematic and methodological analysis, International
Journal of Foresight and Innovation Policy 9(1): 19-38.
http://dx.doi.org/10.1504/IJFIP.2013.051759
Notten, P. van; Rotmans, J.; Asselt, M. B. A. van; Rothman, D. S.
2003. An updated scenario typology, Futures 35: 423-443.
http://dx.doi.org/10.1016/S0016-3287(02)00090-3
O'Keefe, M.; Wright, G. 2010. Non-receptive organizational
contexts and scenario planning interventions: a demonstration of inertia
in the strategic decision-making of a CEO, despite strong pressure for a
change, Futures 42(1): 26-41.
http://dx.doi.org/10.1016/j.futures.2009.08.004
Perechuda, K.; Sobinska, M. 2008. Scenariusze, dialogi iprocesy
zarzqdzania wiedzq [Scenarios, dialogue and processes of knowledge
management], Warszawa: Difin.
Ringland, G. 1998. Scenario Planning: Managing for the Future.
Chichester: Wiley.
Rogut, A.; Piasecki, B. 2008. Regionalna Strategia Innowacji dla
wojewodztwa Lodzkiego [Regional Innovation Strategy for the Lodzkie
Voivodship], RSI LORIS PLUS, Lodz: Spoleczna Wyzsza Szkola
Przedsiebiorczosci i Zarzadzania w Lodzi.
Rogut, A.; Piasecki, B. 2011. Podrecznik ewaluatoraprojektow
foresight [The handbook of foresight projects' evaluator].
Warszawa: Ministerstwo Nauki i Szkolnictwa Wyzszego.
Sacio-Szymanska, A.; Poteralska, B.; Mazurkiewicz, A. 2010.
Zastosowanie metody roadmappingu technologicznego w projektach foresight
[The application of road mapping method in foresight projects],
Zarzadzanie i marketing. Zeszyty Naukowe Politechniki Rzeszowskiej
17(3): 335-346.
Saritas, O.; Nugroho, Y. 2012. Mapping issues and envisaging
futures: an evolutionary scenario approach, Technological Forecasting
and Social Change 79(3): 509-529.
http://dx.doi.org/10.1016/j.techfore.2011.09.005
Sarpong, D. 2011. Towards a methodological approach: theorising
scenario thinking as a social practice, Foresight 13(2): 4-17.
http://dx.doi.org/10.1108/14636681111126210
Stake, R. E. 2009. Jakosciowe studium przypadku [Qualitative case
study] in Denzin, N. K.; Lincoln, Y. S. Metody badan jakosciowych, PWN,
Warszawa, vol. 1, 623-654.
Stewart, C. C. 2008. Integral scenarios: reframing theory, building
from practice, Futures 40: 160-172.
http://dx.doi.org/10.1016/j.futures.2007.11.013
Szewczyk, R. (Ed.). 2008. Foresight wojewodztwa mazowieckiego.
Krzyzowa analiza wptywow, scenariusze rozwoju, priorytetowe technologie
[Foresight for the Mazowieckie Voivodship. A cross analysis of
influences, development scenarios, priority Technologies], [online],
[cited 12 May 2010] Available from Internet: www.formazovia.pl.
Tsoukas, H.; Shepherd, J. 2004. Managing the future, foresight in
the knowledge economy. Bodmin: Blackwell Publishing.
Van der Heidjen, K.; Schutte, P. 2000, Look before you leap: key
questions for designing scenario applications, Scenario and Strategy
Planning 1(6): 20-24.
Vliet, M. van; Kok, K.; Veldkamp, A.; Arkki, S. 2012. Structure in
creativity: an exploratory study to analyse the effects of structuring
tools on scenario workshop results, Futures 44(8): 746-760.
http://dx.doi.org/10.1016/j.futures.2012.05.002
Wojcicki, J. M.; Ladyzynski, P. 2008. System monitorowania i
scenariusze rozwoju technologii medycznych w Polsce [Monitoring System
and Scenarios of Medical Technologies Development in Poland].Warszawa.
Zavadskas, E. K.; Turskis, Z. 2010. A new additive ratio assessment
(ARAS) method in multicriteria decision-making, Technological and
Economic Development of Economy 16(2): 159-172.
http://dx.doi.org/10.3846/tede.2010.10
Zurek, M. B.; Henrichs, T. 2007. Linking scenarios across
geographical scales in international environmental assessments,
Technological Forecasting and Social Change 74 (8): 1282-1295.
http://dx.doi.org/10.1016/j.techfore.2006.11.005
Joanicjusz NAZARKO, Anna KONONIUK
Faculty of Management, Bialystok University of Technology, Wiejska
str. 45A, PL 15-351 Bialystok, Poland
Corresponding author Joanicjusz Nazarko
E-mail:
[email protected]
Received 22 December 2012; accepted 19 May 2013
(1) The notion of triangulation has been described in the legend to
the questionnaire.
Joanicjusz NAZARKO is a Professor at the Bialystok University of
Technology in Poland. He serves as Dean of the Faculty of Management and
Head of the Department of Business Informatics and Logistics. He has
published over 200 publications and a number of expert assessments,
projects and technical and economic elaborations. He was a member of the
Steering Committee of the National Foresight Program "Poland
2020". He has served as an expert of the EU 7th Framework Program.
He is an IEEE senior member. He is a recognised expert in the fields of
forecasting, simulation, foresight and benchmarking.
Anna KONONIUK is a Researcher in the Chair of Business Informatics
and Logistics at the Management Faculty of Bialystok University of
Technology, Poland. She holds a PhD in Management from the Warsaw
University. She was one of the initiators of the Support Group in the
National Foresight Program "Poland 2020". Currently, she is
involved as a member of key research teams in foresight projects of
regional, trade and national type. Her scientific research interests are
forecasting, time series analysis, social network analysis and foresight
methods with an emphasis on scenario analysis.
Table 1. List of sectoral foresight projects in which scenario
method has been applied
Project Project name Sector
number
1 Technological foresight of Polish founding
founding (PF)
2 Technological foresight in the polymer materials
area of polymer materials (PM)
3 Technological development lignite extraction
scenarios of the lignite
extraction and processing
industry (LE)
4 Technological development coal extraction
scenarios of the coal extraction
industry (CE)
5 Development scenarios of metallic, ceramic
metallic, ceramic and composite and composite
material technologies (MCCM) materials
6 Assessment of the perspectives cosmic
and benefits from the utilisation technologies
of satellite and cosmic
technologies development in
Poland (SCT)
7 Directions of material technology aviation industry
development for the needs of
aviation cluster "Aviation
Valley" (AV)
8 Technological development copper
scenarios of copper and
accompanying raw materials
extraction industry in Poland (CO)
9 Monitoring system and development medical
scenarios of medical technologies technologies
in Poland (MEDT)
10 Technological development fuel and energy
scenarios of the fuel and energy industry
complex for the country's
energetic security (FEI)
Table 2. List of the regional foresight projects in which scenario
method has been applied
Project Project name
number
1 Key Technologies for the sustainable development of
slaskie voivodship (SLV)
2 Technological foresight for the sustainable
developement of Malopolska (MPV)
3 Monitoring and forecasting of key, innovative
technologies for the sustainable development of
mazowieckie voivodship (MZV)
4 Loris Vision. Regional technological foresight
(lodzkie voivodship) (LOV)
5 Opolskie voivodship as the region of sustainable
development region al foresight 2020 (OPV)
6 Key technologies for the sustainable development of
swietokrzyskie voivodship (SWV)
7 Key technologies for the sustainable development of
podkarpackie voivodship (PKV)
8 Innovative macroregion. Technological foresight for
the dolnoslaskie voivodship to 2020 (DSV)
Table 3. The key phases of scenario construction in the Polish
foresight projects of regional and sectoral type
Project The key phases of scenario construction/The way of
abbreviation scenario building in the projects
PF Trade consultations with the application of the
Delphi method.
PM 1. Identifying the variants of environment behaviour.
2. Setting the vision of technological development.
3. Assessing the probability of vision occurrence in
each variant.
LE 1. Simulation modelling. 2. Adaptive optimisation. 3.
Variants prioritisation with the use of
brainstorming.
CE 1. A current state diagnosis. 2. Setting the existed
and forecasted external conditions. 3. Description of
innovativeness and prioritisation of the existing
technologies. 4. Scenarios construction of detailed
technologies. 5. Scenarios verification. 6. The
construction of complex scenario of coal extraction
industry.
MCCM 1. Identifying the key factors. 2. SWOT analysis. 3.
Cross-impact analysis.
SCT 1. Trend analysis. 2. Identifying the key factors. 3.
Scenario building.
AV Discussion panels.
CO 1. Analysis of raw materials balance, forecasts and
marginal conditions. 2. The assessment of technology
innovativeness in the sector. 3. Key technologies
identification 4. Delphi study in two rounds.
FEI 1. Identifying the variants of environment behaviour.
2. Setting the vision of technological development.
3. Assessing the probability of vision occurrence in
each variant.
SLV 1. The procedure of linking visions to scenario
variants. 2. The development of a given technology in
the communal/industrial/transport/telecommunication
area. 3. Preparing scenario description for the
research areas. 4. The formulation of general theses.
5. Construction of optimistic, pessimistic scenario
and a technology roadmap.
MPV 1. Diagnosis of the research area. 2. The
organisation of the expert panels. 3. Collecting
opinions and remarks of the panelists.
LOV 1. Identification of future development alternatives
of voivodship. 2. The selection of scenario leading
to the sustainable development of voivodship. 3.
Offering recommendations timing at the increase of
regional innovative policy effectiveness. 4. The
identification of activities leading to priority
technologies development.
OPV 1. Identifying the success factors for each research
area. 2. Construction of optimistic, pessimistic and
business as usual scenario for chemistry sector.
SWV no data available.
PKV Scenarios were constructed by experts during expert
workshops using cross-impact analysis.
DSV Scenarios were constructed by experts who were asked
to present their own proposals of scenarios. Then,
their proposals were assessed during seminars by
business entrepreneurs as well as local and central
administration representatives.
Source: authors' own study.
Fig. 2. Expert structure in chosen regional and trade foresight
projects
SWV AV MCCM SLV OPV PF CO DSV
AC 48% 49% 84,5% 14% 55,5% 80% 65% 55%
BP 8% 49% 9,5% 72% 20% 20% 35% 18%
PCS 20% -- 3% 14% 24,5% -- -- 18%
MM -- -- 2% -- -- -- -- 9%
NON -- 2% -- -- -- -- -- --
OTHER 4% -- -- -- -- -- -- --
Note: Table made from bar graph.
Fig. 3. Expert team structure engaged in scenario building
SWV OPV CO AV MCCM PF
AC 48% 43% 70% 50% 71% 90%
BP 28% 26% 25% 47% 12% 10%
PCS 20% 31% 5% -- 12% --
MM -- -- -- -- 5% --
NON -- -- -- 3% -- --
OTHER 4% -- -- -- -- --
Source: own work based on questionnaire results
Note: Table made from bar graph.
Fig. 4. Time devoted to scenario method employment in Polish
regional and sector foresight projects
Project's Number of months
Acronym
PKV 2
SCT 2
MPV 2,5
LOV 3
MCCM 3
OPV 3
MZV 4
FEI 5
PM 5
PF 6
SLV 7
CO 11
CE 16
LE 25
Source: own work based on questionnaire results
Note: Table made from bar graph.
Fig. 5. The number of scenarios built in the researched
Polish regional and sector foresight projects
Project's Number of scenarios
Acronym built
SCT 3
PKV 3
CO 3
AV 3
PF 4
LOV 4
OPV 6
MZV 8
MCCCM 8
LE 11
MPV 13
FEI 15
DSV 16
SLV 21
CE 36
PM 56
Source: own work based on questionnaire results
Note: Table made from bar graph.
