↑ ALTO ↑
Diparmento di Scienze Economiche, Aziendali, Matemache e Stasche “Bruno de Fine”
Università degli studi di Trieste
Diparmento di Scienze Economiche Aziendali Matemache e Stasche
Impaginazione Gabriella Clabot
© copyright Edizioni Università di Trieste, Trieste 2016
Proprietà letteraria riservata.
I diritti di traduzione, memorizzazione elettronica, di riproduzione e di adattamento totale e parziale di questa pubblicazione, con qualsiasi mezzo (compresi i microfilm, le fotocopie e altro) sono riservati per tutti i paesi.
ISBN 978-88-8303-761-0 (print) ISBN 978-88-8303-762-7 (online)
EUT Edizioni Università di Trieste Via Weiss, 21 – 34128 Trieste http://eut.units.it
https://www.facebook.com/EUTEdizioniUniversitaTrieste This book has been produced with the financial assistance of the IPA Adriatic Cross-Border Cooperation Programme. The contents of this book are the sole responsibility of the PACINNO project partners and can under no circumstances be regarded as reflecting the position
of the IPA Adriatic Cross-Border Cooperation Programme Authorities.
La versione online ad accesso aperto di questo volume
Innovation
in the Adriatic Region
edited by
Cozza, Claudio
Harirchi, Gouya
Marković Čunko, Ana
5
7 Introduction – Closing the innovation gap in the Adriatic Region: the legacy of PACINNO
TRACOGNA, ANDREA
15 Chapter 1 – Methodology
ČIĆEK, FILIP; MARKOVIĆ ČUNKO, ANA; GERBIN, ANI
25 Chapter 2 – Albania
DEMO, ERVIN; DIBRA, SIDITA; JAUPI, FATMA; GRABOVA , PERSETA; BESHKU, BLERINA
43 Chapter 3 – Bosnia and Herzegovina
ARSLANAGIĆ-KALAJDŽIĆ, MAJA; TURULJA, LEJLA
61 Chapter 4 – Croatia
ČIĆEK FILIP; BEGONJA, MARTA; MARKOVIĆ ČUNKO, ANA; GERBIN, ANI
81 Chapter 5 – Greece
PATELI, ADA; MIKALEF, PATRICK; MYLONAS, PHIVOS; VARITIMIDIS, CHRISTOS; KERMANIDIS, KATIA; ANDRONIKOS, THEODOROS
101 Chapter 6 – Italy
BALBONI, BERNARDO; BORTOLUZZI, GUIDO; COZZA, CLAUDIO; HARIRCHI, GOUYA; PUSTOVRH, ALEŠ
123 Chapter 7 – Montenegro
KARADŽIĆ, VESNA; DROBNJAK, RADIVOJE; BOŠKOVIĆ, VELIBOR
147 Chapter 8 – Serbia
JANEV, VALENTINA; PAUNOVIĆ, DEJAN; JOVANOVIĆ-VASOVIĆ, JELENA; ORČEVIĆ, SRĐAN; VRANEŠ, SANJA
167 Chapter 9 – Slovenia
ŽUPIĆ, IVAN; ČERNE, MATEJ; RANGUS, KAJA; TOMAT, LUKA; ALEKSIĆ, DARIJA; BOGILOVIĆ, SABINA
189 Chapter 10 – Innovation policies in the Adriatic Region
CAPELLARI, SAVERIA; COZZA, CLAUDIO
7
Introduction
Closing the innovation gap
in the Adriatic Region:
the legacy of PACINNO
the adriatic ionian region and its long-standing problems
In the last few years, the European Union has been considering the Adriatic Ionian Region as a target area for support actions and assistance, with the main goal being to assure its economic and political stability, stabilise democracy levels, and devel-op sustainable economic growth and employment.The Region is affected by severe structural economic problems and obstacles, i.e., poor infrastructure, weak research funding and weak innovation framework conditions, scarce connections between academia and business, fragmentation and limited size of domestic markets, and nonhomogeneous regulatory regimes. Such contextual factors result in scarce entrepreneurial activity in key industries, low rates of new venture creation (particularly in science and technology-based sectors), limited business size, small scale of investments, and firms’ lower inno-vation attitude.
Overall, the Adriatic Ionian countries appear to be stuck in their position due to their relative closure to outside influences, and their limited capacity to absorb new knowledge coming from the external (scientific and business) world. The ex-treme political fragmentation is also unhelpful and the significant cultural
differ-ANDREA TRACOGNA
University of Trieste, PACINNO Project Leader
INTR
8
ences also create obstacles. Despite the significant past accomplishments of some localised contexts (e.g., North-east Italy and Slovenia), the Adriatic Ionian Region as a whole suffers from a severe lack of competitiveness, which can eventually – if not appropriately addressed - undermine its economic growth and integration at the European level and maintain instability in, and migration from, the EU’s south-eastern neighbourhood.
the adriatic ionian region as an innovation ecosystem
One of the main characteristics of innovation today is its tendency to trespass the boundaries of single companies or institutions, to take place across sectors, indus-tries and counindus-tries, and to be fed by and produce streams of knowledge that circu-late rapidly from localised areas to the global arena.
It has, then, just been natural for us to conceive of the Adriatic and Ionian area as potentially a single innovation macro-system. Indeed, the presence in the area of both Member and non-Member States offers the possibility to explore the poten-tial for effective transfer of policies, actions, and practices from different groups of countries. In particular, there are clusters of innovation where advanced practices and policies of innovation management at the macro and micro level have already been implemented (such as North-east Italy and Slovenia) and which can facilitate the transfer of best practices to relatively less developed areas.
With reference to research and innovation, the Adriatic Ionian area is character-ised by low levels of investment and the lack of competitiveness and technological capacity of SMEs, which are mostly oriented towards domestic markets. With the aim of opening markets to more competitive and innovative models, especially to face the effects of the current economic crisis, it seems necessary to develop new policies that foster research and innovation and that give priority to investments in firms directly linked to research and innovation.
9
INTRODUCTION
pacinno: its mission and approach
PACINNO considers innovation as an open process that crosses businesses, coun-tries and industry borders. This justifies our interest in exploring innovation eco-systems, in understanding and leveraging on the roles of different actors, and in the main determinants of innovative performance at national and regional levels. Our main aim has been to carry out precise actions/policies in favour of the project target groups, and who are as follows:
1. Established and new SMEs, operating both in science-based, high-tech settings and in traditional sectors. They are the natural beneficiaries of technology trans-fer activities carried out by the research organisations and represent the demand side of innovation.
2. Highly skilled researchers that have the potential to become the initiators of high-tech start-up companies and who will receive business and entrepreneurial support services.
3. Public and private institutions whose mission is to support innovation and tech-nology-based start-up ventures. They include incubators, accelerators, clusters and technology transfer offices but also political bodies such as municipalities, provinces, administrative regions, and national governments in charge of set-ting the political agenda for innovation and economic development.
10
this book: mapping the adriatic ionian innovation system
and policies
Various editions of the Innovation Union Scoreboard testify to the existence and persistence of a strong innovation gap in the Adriatic Ionian area is . The Region’s Member States (Italy, Greece, Slovenia and Croatia) rank below the EU average, with only Slovenia entering the category of “innovation followers”. Only recently, Serbia has been included in the group of “moderate innovators”, while no evidence is pro-vided on the other countries of the area: Bosnia and Herzegovina, Albania, Monte-negro. These countries appear in another composite indicator: the Global Innovation Index (GII). In the 2015 edition, Albania was given a score of 0.39 (the maximum is 1 = Switzerland), while Bosnia and Herzegovina got 0.44. Based on the same indica-tor, Montenegro is performing better than Serbia and Greece.
To get a more granular view of both the innovation gaps and of the potential of the Region, PACINNO has carried out a comprehensive mapping of innovation systems in the Adriatic Ionian area by collecting a wealth of indicators from across ten different dimensions. This mapping tool (http://www.adriaticinnovationmap. eu) mostly uses secondary data – often directly from the Eurostat, or other sources such as the GII – complementing them with specific indicators on the three Adriatic countries for which they are usually missing: Bosnia and Herzegovina, Albania and Montenegro.
The maps identify a strong gap in the area concerning the human resources em-ployed in science and technology. Only Slovenia ranks better than the EU average in terms of R&D employees and researchers per active population. However, in abso-lute values, this means just 21,000 and 9,000 persons, respectively. The real gap, for all countries, resides in the very limited absolute number of people involved in the R&D process: only 800 researchers are active in Albania and 400 in Montenegro. Such a gap, in terms of talents and skills, is also reflected in the low scientific out-put of the Region. For instance, recent figures from the World Intellectual Property Organization (WIPO) report just four patent filings for Albania and 15 for Bosnia and Herzegovina and the SCImago Journal Rank reports very limited numbers of publi-cations from Albania, Bosnia and Herzegovina and Montenegro.
However, significant potential for the area resides in the trends for highly skilled human resources and higher education that have developed in recent years. For in-stance, all countries in the area have a relatively good number of tertiary-educated people, as well as a growing number of PhDs. New PhD graduates could easily in-crease the bulk of prospective research and innovation actors in the area.
in-11
INTRODUCTION
vestment in R&D is still very limited, although, as a share of GDP, Slovenia performs better than the EU average; Croatia, Greece and Serbia also show values very close to the EU average. Also, there are few newly established companies, despite the relatively promising environment. Indeed, the World Bank’s Doing Business figures tell of an entire Adriatic Ionian area performing well in crucial indicators such as the “ease of starting a business” and “ease of protecting investors”.
PACINNO has generated new empirical evidence on innovation not only at the macro-level, but also at the firm level. More than 1,000 questionnaires have been collected from SMEs in the Adriatic area, aimed at detailing their innovation be-haviour. The questionnaires are largely comparable to the Community Innovation Survey (CIS) and provide very interesting insights. With reference to the link be-tween innovation performance and inter-firm collaboration, Italian SMEs collab-orating with partners from other Adriatic Ionian countries have significantly im-proved their exporting performance. On the other hand, for non-Italian firms, both domestic collaboration and intra-EU collaboration are significantly enhancing their innovation performances.
As regards R&D expenses, the findings show that inward and external R&D ex-penditures, analysed as a percentage of sales turnover, vary significantly across industries. Overall, there is a tendency for both high-tech and low-tech firms to allocate a limited amount of resources to R&D, both inward and external, as com-pared to the European average (above 20% of sales turnover (CIS, 2012)), with only Slovenia, Bosnia-Herzegovina, Serbia, and Albania overcoming the threshold of the 10% of inward R&D.
As regards innovation performance, the high-tech firms in the Region show a sig-nificant propensity to introduce new products, particularly in Bosnia-Herzegovina, Albania, Italy, and Slovenia, while the introduction of innovative products is less fre-quent for the high-tech firms of Greece, Croatia and Montenegro. The data also reveal that the firms’ innovation levels are not always related to the market performance. Indeed, on the one hand, several highly innovative firms in the Region have only achieved a narrow market scope; on the other hand, many low-tech firms - particular-ly in those countries characterised by traditional manufacturing sectors such as Itaparticular-ly and Greece - have been able to significantly expand their markets and sustain growth.
12
A goal of PACINNO has been to develop a comprehensive taxonomy of the inno-vation policies adopted at both national and sub-national levels. Another goal has been the identification of best practices that could easily be replicated in the area. Indeed, rather than using world-class experiences as a benchmark, it is believed that a set of “regional best practices” should become a reference point for promot-ing innovation in the Region. Evidence compromot-ing from the PACINNO project – includ-ing interviews with policymakers from all countries – suggests that a bottom-up approach should be followed for both listing the existing policies in the area and developing a meaningful taxonomy.
what next?
We believe that the potential for innovation and economic development in the Adri-atic Ionian Region lies in a more effective connection between the academic and research institutions, the small and medium sized enterprises (SMEs) and the policy makers, in both traditional and high technology sectors. The establishment of an effective innovation ecosystem at the Adriatic Ionian level should follow the lines traced below:
• Towards an Adriatic Ionian network of research centres. After hav-ing successfully set up a platform for trans-academic cooperation in innovation, and having carried out several initiatives aimed at promoting innovation at the micro (firm) level, the challenge of the PACINNO partnership is to assure its sustainability after the formal expiration of the project (November, 2016). In this respect, Netval, the Italian association for the valorisation of results from public research, is consid-ered to be the best practice of reference. Its members include 54 Italian universi-ties, and 5 public research organisations, representing 66.3% of Italian universiuniversi-ties, 75.7% of Italian students and 80.4% of university professors. Founded in 2002, Netval’s mission is to be the “research interface” for Ministries and local admin-istrations, industrial associations and industries, venture capitalists and financial bodies, and to promote the role of public research in innovation processes. Netval has contributed to the homogenisation of technology transfer (TT) protocols and procedures among universities and to the emergence of standards in the collabora-tion with industry. The associacollabora-tion has been playing a pioneering role in building TT indicators and is currently collaborating with Italian ministries about these topics.
13
INTRODUCTION
Region, rather than just focusing on the promotion of new sectors and entrepre-neurial activities. We firmly believe that the Region’s innovation potential in tra-ditional industries is not lower than that in the high-tech industries. Furthermore, no significant innovation improvement can overlook the SMEs. In this respect, our aim is to find a balance between the Smart Specialization Strategies defined at the national-level and the unexploited potential of the thick fabric of service and man-ufacturing activities of the Region. Innovation policy-makers should not disregard key sectors such as agriculture, agro-food, tourism, and the blue economy. Also, SMEs’ adoption of high-impact enabling technologies (such as digital technologies and new manufacturing techniques) should also be promoted and incentivised in the traditional industries.
15
METHODOL
OGY
The main goal of the PACINNO project is to establish a platform for cooperation in research and innovation on the level of the Adriatic Region, with the aim of over-coming the main inhibitors to economic development. To this end, it is of crucial importance to fully understand the factors that enable and inhibit the growth and development of an innovation-friendly climate in the Region. In order to address this issue, all eight countries of the Region conducted a micro, meso and macro-lev-el analysis of innovation in their respective countries. In-depth micro-levmacro-lev-el research has been conducted in order to fully grasp individual perspectives on innovation. Furthermore, to understand organizational perspective of innovation, meso-level research was conducted, which included two research methods: survey and action research. Finally, in order to understand macro levels of innovation in the Adriatic Region countries, two types of data were utilised: quantitative and qualitative.
Moreover, it is important to highlight that this book is a result of several coun-try-level analyses that were collected in the form of a report. Therefore, the content is unified and follows the same structure for all eight countries of the Region.
ČIĆEK FILIP; MARKOVIĆ ČUNKO, ANA; GERBIN, ANI
MEDRI, University of Rijeka, Faculty of Medicine
Chapter 1
16
1.1 macro level research
One of the main outputs of the macro level analysis on the regional level is the creation of the Adriatic Innovation Map. In order to obtain more information on this please visit the Adriatic Innovation Map web site: www.adriaticinnovationmap.eu.
In the PACINNO project, the macroeconomic analysis of innovation enablers and inhibitors was conducted from both the qualitative and the quantitative perspec-tives. The quantitative analysis was used to identify and classify the macro-level enablers and inhibitors.
1.1.1
macroquantitativeanalysisFollowing the review of various empirical studies on national and regional innova-tion systems and screening of numerous internainnova-tional (EUROSTAT, World Bank, Total Economy Database, Innovation Union Scoreboard, OECD, Global Innovation In-dex, EU CORDIS, eCORDA, Global Entrepreneurship Monitor, SCImago) and national databases, a total of 226 innovation indicators, which can be viewed as enablers or inhibitors, were pre-selected and grouped into ten categories or “dimensions”. The data were collected by all project partners during the period from July to November 2014, and were again revised and updated in October 2015.
However, it must be noted that a significant amount of data could not be col-lected, especially for the non-EU countries of the Adriatic Region, due to their non-availability, even from local statistics offices. In order to tackle this problem, the following selection procedure was applied: (1) if there were more than two coun-tries’ data missing for any of the observed years per variable, the variable was disre-garded; (2) if there was a minimum of one year of observation with sufficient data (with not more than two missing), the variable was considered for analysis. This process resulted in 33 indicators selected for the analysis, with the data referring to the period from 2011 until 2014. Table 1.1 summarises the macro-level innovation study dimensions and relevant indicators.
Finally, due to space limitations, for the purposes of this book we have considered a total of six indicators for the analysis: GDP per capita (economic data), the num-ber of new PhD graduates (human resources), the total numnum-ber of students/tertiary education participation (education system), government expenditure on R&D in the country (public sector), business expenditure on R&D in the country (private sector) and the number of SCImago scientific journal articles (scientific output).1
17
1. METHODOLOGY
Table 1.1 – Innovation dimensions with selected indicators2
No. Dimension Indicators
1 Economic data GDP per capita
(in EUR)
2 Human resources Total number of new PhD graduates
(% of active population)
3 Education system Total number of students/tertiary education population
(% of active population)
4 Public sector Government expenditure on R&D in the country
(% of GDP)
5 Private sector Business expenditure on R&D in the country
(% of GDP)
6 Scientific output Number of SCIMAGO scientific journal articles
(% of active population)
The dimension of economic data measures some key indicators of the overall na-tional economic situation and performance. The second dimension is oriented to-wards human resources, which play a critical role in the innovation process, as the competitive advantage built on human resources is not easily imitable. The educa-tion system is considered to play a central role in building innovaeduca-tion capacity, serv-ing as a vehicle for transferrserv-ing knowledge and earnserv-ing competences. In the fourth dimension, the analysis focuses on several indicators of public sector commitment to the generation of new ideas. The fifth dimension represents the private sector, which is considered to be an engine of economic growth and job creation because of the constant upgrading and adjustments that private enterprises have to make in order to stay competitive, thus incorporating innovation and new technologies. Closely related to the innovation capacity is the scientific output, which is also used as an indicator of a country’s innovation performance.
The data were analysed using descriptive statistics. Considering that it was not always possible to compare the data by the same year, the arithmetic mean value of the last three available years of observation was calculated for every se-lected variable.
18
1.1.2
innovationpoliciesmappingIn order to get a perspective on innovation policies, partners performed a search of the ERAWATCH webpages and reviewed the documents related to their countries. Based on the obtained information, a list of R&D and innovation policies for the period from 2007-2013 (coincident with the FP7 period) was created.
The second step, after the identification and description of institutions respon-sible for innovation policies, was the identification and description of particular innovation policies. This was also done through desk research of laws/regulations promoted by the identified policy making institutions. Researchers were encour-aged to read every document carefully or even consult with the responsible bodies if necessary.
The final taxonomy of policies was developed by the joint efforts of the consor-tium and included the following variables:
1. Category in the taxonomy (further divided into direct (various grants) or indirect (various incentives) support:
• R&D
• Human Resources • Collaboration
• Innovation capabilities
2. Name of the tool/measure and/or its code 3. Responsible body
4. Time span • Start/end years 5. Short description
6. Specific target groups (if applicable) 7. Best practice example (yes/no)
1.1.3
interviews19
1. METHODOLOGY
same time, it is important to have some structure in order to enable comparison between countries. The interviews were conducted to the point of saturation, where additional interviews do not contribute to findings by giving us some new insights (Kvale, 1996).
Before conducting the rest of the interviews, researchers from every participat-ing country conducted two pilot interviews in order to test the clarity and appro-priateness of the whole interview process. An interview guide was used to lead the researchers, which was prepared on the basis of the literature review and various reports on innovation systems and policies. The interview was divided into two main sections. The first section was oriented toward the general overview of inno-vation measures, instruments and actors, and the second focused on best practice examples of innovation policies. The interviews were conducted from June until October 2015.
SAMPLE SELECTION
For the qualitative interviews, respondents were selected using the reference-based method. This means that the potential respondents were selected on the basis of their specific position and knowledge on the subject. In addition to the refer-ence-based method, the snowball (or chain sampling) method was used. The re-spondents were asked to identify other relevant rere-spondents who were then select-ed basselect-ed on their relevance to the research (Patton, 1990).
On the level of the Adriatic Region, a total of 50 interviews were conducted. The first contact with the respondent was made via e-mail which explained the purpose of the research, why the respondents were chosen, the researcher’s affiliation and the general aims of the project. In addition, an invitation letter was attached that further explained the subject of the interview and its contents.
The final sample consisted of four main groups of respondents: entrepreneurs, policy makers, academics and intermediaries.
DATA COLLECTION AND ANALYSIS
Face-to-face interviews were used to collect the data with both sides signing the consent form (Kvale, 1996; Yin, 2011). The consent form contained information about the interview, its structure and guaranteed confidentiality. Anonymity was also ensured by coding the respondents’ names and affiliations in all of the inter-view-related materials. The research team audio-recorded the interviews and later extracted written summaries from the recorded material, which served as a basis for data analysis.
20
guiding the interview and the other for taking notes and making sure that the struc-ture was followed and every topic covered.
The ad hoc creation of meaning method was used for the interview analysis (Kvale, 1996). This method implies that the researchers were free to choose the analysis technique depending on the research phase, level of analysis and other factors. Since the respondents came from different contexts and had different ap-proaches to the same phenomenon, this method was estimated as the most appro-priate for the analysis.
The data analysis was done using the Atlas.ti software. It was used to assign codes, code families and themes to the audio recordings and transcribed summa-ries. Code families were designed according to the interview structure and were later accompanied by specific codes assigned to them according to the questions from the interview structure.
1.2 meso level research
3In order to study the meso-foundations of innovation in the Adriatic Region we have conducted a survey.
1.2.1
survey4The Community Innovation Survey (CIS) is commonly used as the most compre-hensive source of data for the analysis of innovation at the European level. CIS is formed as a complex of several different surveys that are conducted by the national statistics offices in Europe. Since this tool represents a unified research instrument, it enables direct comparisons of countries, sectors or regions. The CIS survey is also the main source of data for the Innovation Union Scoreboard (IUS). The IUS serves as a main tool for the European Commission to assess the innovation performance of the EU member countries.
Regardless of its comprehensiveness, the IUS still does not cover many coun-tries of the Adriatic Region. In particular, it partially covers Serbia, but it does not cover Bosnia and Herzegovina, Montenegro or Albania. In order to fill this gap, the intention of the PACINNO research team was to use a comparable instrument rely-ing heavily on the CIS structure. For the purpose of the PACINNO study, the
ques-3 For more information regarding the meso level analysis see PACINNO 4.1 Report on micro founda-tions of innovation (survey on innovative companies) available at www.pacinno.eu.
21
1. METHODOLOGY
tionnaire was developed partially using the CIS methodology and adding additional questions derived from the academic literature.
The final version of the questionnaire was comprised of 12 sections with the focus areas presented in Table 1.2.
After the first English version of the questionnaire was completed, researchers applied the back translating method, which refers to translating the questionnaire into the local languages and back into English, all using different translators, fol-lowed by correction of irregularities.
The final version of the questionnaire was posted on the Limesurvey (www. limesurvey.com) platform, hosted by the School of Economics and Business, Sara-jevo (WP4 lead partner).
The survey was conducted between July 2014 and January 2015 and most ques-tions refer to the period from 2011- 2013. The results were interpreted using descrip-tive statistics.
Table 1.2 – Focus areas of the meso-level analysis survey
Section Focus
1 General information about the enterprise including its NUTS, main activity and NACE,
and market presence (national, Adriatic Region and above)
2 Product (goods or services) innovation in terms of introduction of new or significantly improved goods or services, both new to the market and new to the firm
3 Process innovation of firms, defining process innovation as a new or significantly improved production process, distribution method or supporting activity
4 Factors hampering product and process innovation activities
5 Implementation of in-house R&D, external R&D and the level of spending on those activities
6 Sources of information and cooperation for product and process innovation and
cooperation between firms and their potential partners
7 Organisational innovation
8 Process (administrative/marketing) innovation
9 Self-reported performance measure (compared to the most direct competitor)
10 Firmographic data
11 Social innovation
22
1.2.2
samplinganddataA stratified random sampling method was used in all countries of the Adriatic Re-gion. This implies selecting subsets of the overall population of micro, small and medium firms and then randomly selecting a sample from those subsets. In the case of the questionnaires, subsets were selected from the innovative industries in each country. Researchers from each country decided upon the appropriate in-dustry. For some countries, official secondary data on the most innovative indus-tries existed, while for some they did not and the decision was made based on prior qualitative research and assessment. In case this described sampling method was not technically and objectively viable in a country, researchers were free to select another sampling method, trying to take into account the general criteria.
Following the distribution of the survey, a total of 1.165 responses were selected for analysis based on a 70% completion rate (cut-off criteria).
1.2.3
limitationsAlthough all the PACINNO project partners carefully followed the sampling and data collection procedures defined at the consortium level, alternative approaches had to be taken in some countries, which was mostly due to the absence of adequate official business registries. Therefore, some caution should be exercised in interpreting the results for the whole Adriatic Region, taking into account the varieties of the samples.
1.3 micro level research
5In-depth micro-level research was used in order to efficiently grasp individual per-spectives on innovation.
The initial plan set out in the project proposal included the analysis of 16 firms, 2 per participant country. Since 20 firms were ultimately analysed, the consortium exceeded the project plan by 25% in terms of outputs. Quantitative data were collect-ed on the level of individual employees. Statistical inference was analyscollect-ed via SPSS 20 software. The research was conducted using the questionnaire instrument, which contained 14 sections and was translated using a back-translating method. The ques-tionnaire was distributed to respondents during November and December 2014.
23
1. METHODOLOGY
Table 1.3 below presents the measured concepts in the research on individu-al-level innovativeness.
The data were collected from the employees for the individual level analysis, but the questionnaire also included questions about their group/team/unit belonging. Each project partner made efforts to find suitable innovative SMEs that agreed to participate in the research. The questionnaires were distributed to their employees online or in paper format. The final database comprised of 8 countries, 20 firms, 73 groups and 787 individual cases.
Table 1.3 – In-depth micro-level analysis: measured concepts from the individual-level innovativeness model Section Focus 1 Knowledge hiding 2 Uncertainty avoidance 3 Individualism 4 Individual innovation 5 Employee silence
6 Time pressure perception
24
1. Kvale, S. (1996). Interviews: An introduction to qualitative research interviewing. Thousand Oaks, California: Sage Publications.
2. Neergaard, H., & Ulhoi, J. P. (Eds.). (2007). Handbook of qualitative research meth-ods in entrepreneurship. Cheltenham, UK; Northampton, MA: Edward Elgar Pub. 3. Patton, M. (1990). Qualitative evaluation and research methods. Beverly Hills,
California: Sage.
4. Yin, R. K. (2011). Qualitative research from start to finish. New York, London: The Guilford Press.
25
ALBANIA
DEMO, ERVIN; DIBRA, SIDITA; JAUPI, FATMA;
GRABOVA, PERSETA; BESHKU, BLERINA
University of Tirana, Albania
Chapter 2
Albania
highlights
• Albania is a country on the Balkan peninsula with a long Adriatic and Ionian coastline, between Greece in the south and Montenegro and Kosovo to the north.
• The economy of Albania has remained limited, but positive growth during the recent global financial and economic crisis.
• The sectors with the best potential for growth are agriculture, ICT services, tourism, the mining industry, renewable energy, manufacturing, transport and logistics.
• Albanian GDP per capita reached 3.605 EUR in 2014.
• In terms of internationalisation, most of the surveyed companies in Albania are present onlyin the domestic market and they mostly export their products in the Adriatic Region, considerably less on the markets of the neighbouring countries in Western, Central or Eastern Europe.
• The levels of support from both local and regional authorities and from the European Union is low in Albania. The percentage of respondents that received support from the central government in Albania is slightly higher than the Adriatic Region average. • Regarding the micro determinants of innovation, knowledge hiding in Albania is not a
common occurrence, as it stands at the level of 1,84, which is lower than the average in the Adriatic Region (2,31).
26
2.1 general overview
Albania is a country on the Balkan peninsula in Southeastern Europe, with a long Adriatic and Ionian coastline, between Greece in the south and Montenegro and Kosovo to the north. After World War II, Albania became a Stalinist state and re-mained isolated until its transition to democracy after 1990. The 1992 elections end-ed 47 years of communist rule and establishend-ed the multiparty democracy.
According to the 2011 Population and Housing Census, the resident population in Albania was 2.821,977. The population has declined by about 8% over the last ten years (INSTAT, 2011), mainly due to high rates of emigration. Many Albanians left the country in search of work; the remittance remains an important source of revenue. Along with other Western Balkan countries, Albania was recognised as a potential country for EU membership in 2003. A Stabilisation and Association Agreement (SAA) entered into force on 1 April 2009. The European Commission rec-ommended that Albania should be granted EU candidate status in October 2013 and it reconfirmed the recommendation in the Progress Report published in June 2014.
Albania still needs to meet the key priorities for EU membership with a particu-lar focus on administration and judiciary reform, fundamental rights, and the fight against corruption and organised crime. Moreover, a constructive and sustainable political dialogue remains essential to consolidate and continue reforms. Despite difficulties, the Albanian Government has built a strategic vision to transform the country’s economy from a low productivity, informal and import dependent econo-my to a modern, innovative and highly productive one.
The economy of Albania has remained limited, but positive growth during the recent global financial and economic crisis. The sectors with the best potential for growth are agriculture, ICT services, tourism, the mining industry, renewable energy, manufacturing, transport and logistics (AIDA, 2015). The overall industrial and trade performance is characterized by a lack of economic competitiveness. Among main elements hampering competitiveness are the lack of a specialised and skilled labour force and a large informal economy. According to the Global Competitiveness Re-port 2014-2015, Albania is ranked in 97th position out of 144 countries, losing eight positions from 2012-2013. In terms of labour market efficiency, the country ranks 93rd, while in innovation it is 120th (World Economic Forum, 2014-2015). In terms of the general socio-economic development, as measured by the Human Development Index (HDI), the country figures in the ‘high human development’ category, ranking 95 out of 187 countries and territories in 2014; this was down 25 positions when compared to 2012 (UNDP, 2014).
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2. ALBANIA
girls and women. The unemployment rate in Albania (for the age-group 15-64 years old) is 17.9% (INSTAT, 2014). Youth unemployment (aged 15-29) remains a crucial issue, since the rate has continuously increased from 21.9% in 2011 to 32.5% in 2014 (INSTAT, 2015).
Women in Albania continue to be under-represented in employment and the gender wage-gap is still wide (Miluka, 2011). They are less present in almost every employment sector in the country (INSTAT, 2014b). Census 2011 data shows that the rate of unemployment among Roma and Egyptian minorities remains high due to low educational qualifications and discrimination.
Albania is finalizing the National Strategy for Development and Integration, among other priorities, presenting innovation as a driving force for increasing com-petitiveness. Industrial parks will provide one of the preconditions for a transition from the present-day economic model, characterized by the use of a low or semi-skilled labour force and the manufacture of products with low added value, to a more innovation-driven and knowledge based development model. To ensure a suc-cessful transition to innovative development, increasing support will be provided to Albanian enterprises that are seeking to modernize their technology by transfer-ring and absorbing (in cooperation with academicians and researchers) innovations currently being applied in other countries or in other local enterprises. Innovation should become a key source of growth and added value even in traditional and rela-tively low-technology sectors, such as agriculture, food processing, industry, trans-port, construction and light industries.
2.1.1
overviewoftheeconomicsituationinthecountryAccording to the World Bank’s estimation, Albania classifies as an upper middle-in-come country, which has undertaken important steps toward establishing a credible market economy over the last twenty-five years. The country has generally been able to maintain positive growth rates and financial stability, despite the ongoing international economic crisis.
2.1.2
overviewoftheresearchandinnovationactorsandactivities inthecountry28
STRATEGIC POLICY MAKING AND PRIORITY SETTING ACTORS
As Albania is a Parliamentary Republic, there are at least three committees respon-sible for research and innovation laws:
• Education and Means of Public Information Parliamentary Committee; • Productive Activity, Trade and Environment Parliamentary Committee; • Economy and Finance Parliamentary Committee. Following the calendar of
dis-cussions, the laws presented at these committees are widely discussed with in-terested actors.
ADVISORY BODIES
There are two main important institutions operating as advisory bodies that report to the Assembly:
• The National Council for Higher Education and Science (NCHES) has been estab-lished as an advisory body to the Council of Ministers (CoM) and the Ministry of Science and Sport (MSS).
Figure 2.1 – Institutions responsible for R&D and Innovation Policy making in Albania
Parliament Enterprises Higher Education Institutions Ministerial Research & Innovation Institutes
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2. ALBANIA
• The Albanian Academy of Science (AAS) was substantially reduced in size after the reform in 2009.
POLICY DESIGN INSTITUTIONS
• The Council of Ministers (CoM) submits draft laws on national scientific activi-ties to the Parliament.
• The Ministry of Innovation and Public Administration (MIPA) is responsible for designing and coordinating policies in the field of information technology and electronic communications, geo-space information infrastructure, postal services, audiovisual media and reformation and modernization of public administration. • The Ministry of Education and Sports (MES) is the main government institution
responsible for scientific research and development policies.
• Other ministries such as the Ministry of Economic Development, Tourism, Trade and Entrepreneurship (MEDTTE); the Ministry of Agriculture, Rural De-velopment and Water Administration (MARDWA); the Ministry of Health (MH); the Ministry of Environment (ME); the Ministry of Transport and Infrastructure (MTI); the Ministry of Defence (MD) and the Ministry of Culture (MC) design policies based on evidence produced by the institutions depending on them, as described below.
POLICY IMPLEMENTATION
• Agency for Research, Technology and Innovation (ARTI); • Authority for Electronic Certification (AEC);
• General Directorate of Patents and Trademarks (GDPT); • Albanian Investment Development Agency (AIDA); • Business Relay and Innovation Centre (BRIC); • Agency for Information Society (AIS);
• Albanian Cyber Incident Response Agency (ALCIRT); • Authority of Electronic and Postal Communications (AEPC); • Agency for Medicaments and Medical Equipment (AMME).
RESEARCH AND INNOVATION INSTITUTES
Research and innovation institutes depend on ministries, as follows: • The State-owned Higher Education Institutions (SHEI);
30
INDEPENDENT RESEARCH AND INNOVATION INSTITUTES • Non-Government Research Entities;
• Private enterprises operating in the field of knowledge and technology transfer and IT.
2.1.3
recentchangesinr&
dandinnovationsysteminthecountryRecent developments in innovation policies have showed signs of stagnation. In recent years Albania has performed poorly, despite having clear objectives related to innovation and research, objectives previously set by the EU.
After an initial momentum that gave a jolt to the Albanian economy, including legislative work, investments that made ICT penetration possible among business-es and individuals, through adopting succbusiness-essful practicbusiness-es and friendly businbusiness-ess pol-icies across the country, has come to a stand still.
Re-organizing the Academy of Science, creating a National Strategy of Innovation and a new agency called the Agency for Research, Technology and Innovation (ARTI) have not made enough to offset the poor performance in technological foreign direct investment (FDI) and to shift businesses strategy from buying innovation into the market rather than developing it internally for sustainable growth. Albania even has a Ministry of Innovation, despite all of these small agencies and public institutions.
The main reason for this situation is the lack of smart and sustainable growth foundations, which is achievable through building safe business environments with an efficient legal framework, and what is most important, a good quality ed-ucation system.
The main policy innovation milestones are not that recent. Nevertheless, the National Strategy for Development and Integration was approved in 2008, as was the National Strategy for Science, Technology and Innovation. One of the main inno-vation policy agencies, the Albanian Investment Development Agency (AIDA), was set up in 2010. The actor list of innovation policy also includes various agencies such as the Business Relay and Innovation Center (BRIC) created in 2011, the National Agency for Information Society (NAIS) and many others.
31
2. ALBANIA
2.2 macro-level analysis of innovation enablers and
inhibitors
In this section, the most relevant macro-indicators of innovation in the country are presented1. These indicators concern six categories of the national innovation
sys-tem: the economic situation of the country, figures regarding human resources as well as the education system, the innovation investments made by both the public and private sectors, and the scientific output. The indicators are synthetically rep-resented in Figure 2.2 and described after that. In the figure, 100 represents the EU average, while the dotted part of the histograms shows the Adriatic region average.
Figure 2.2 – Albanian Innovation System, selected indicators
The economic data include general economic figures of the country, such as GDP per capita, total exports, unemployment rate, current account deficit, etc. The Albanian GDP per capita places the country rather low, in comparison to the Adriatic Region average as well as the EU-28 average.
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The human factor plays a critical role in innovation, as the competitive advantage built on human resources is not easily imitable. Albania has considerably lower hu-man resources indicators in comparison to the regional and EU-28 mean. As ex-pected, considering the country’s size, the total number of new PhD graduates in Albania is very low compared with the Region and EU-28 mean. As a percentage of the active population (15-64 years), the total number of new PhD graduates is still lower than regional and EU-28 level, but it differs by only one percentage point. Education is quite important in this macro analysis because universities represent the environment where most research and innovation activity takes place. In rela-tive terms, the participation in tertiary education has improved and the country’s rates are higher than across the Adriatic Region and the EU-28. This was mainly the result of Albania’s higher education liberalization policy, up until 2015. Lately, en-rolment in tertiary education is limited since the system is being reformed towards higher quality.
The public sector is a part of the economy that consists of state-owned institu-tions, including nationalized industries and services provided by local authorities. Albanian expenditure in R&D is very low in Albania and this was indicated many times as one of the key reasons for the low performance in terms of sourcing inno-vation. In relative terms, as a percentage of GDP, EU-28 member states invest more on R&D than Albania and the Adriatic Region do, on average.
Private enterprises are the main source of innovation and an engine of economic growth and job creation, since commercial enterprises constantly incorporate new technologies in their businesses due to market pressures and an imperative to stay competitive. Data on business expenditure on R&D in the country show that Alba-nian private sector investment in R&D is more than 260 times lower than the aver-age regional spending and represents only 0.08% of GDP.
33
2. ALBANIA
2.3 meso-level analysis of innovation enablers
and inhibitors
The survey of innovative companies in Albania was based on a sample covering all the country area. A total of 870 companies were randomly selected by a database provided by the National Institute of Statistics with innovative or potentially in-novative organisations. Furthermore, 440 companies were randomly selected with sample characteristics based on NACE Rev2 of 50% production (C-manufactur-ing; D-electricity, gas, steam and air conditioning supply; E-water supply, sewer-age, waste management and remediation activities; and F-construction) and 50% services (J-information and communication companies; K-financial and insurance activities; M-professional scientific and technical activities; N-administrative and support service activities; and P, Q-education and human activities). The sample was composed of 15% micro, 35% small and 50% medium size enterprises.
After the first contacts, only 85 companies of the sample agreed to collaborate and fill the questionnaire. Other companies from the initial database were contact-ed, with the goal of preserving the initial sampling based on size, sector and clas-sification. Finally, 106 questionnaires were completed, mainly through face-to-face interviews. Only 20% of responses were gathered through online LimeSurvey, after a short introductory meeting. Direct contacts with company representatives were necessary to ensure a clear understanding of the research scope and some of the concepts used.
During the research process, no methodological difficulties were encountered. The researchers were directly involved in filling in the questionnaire. Although this was time consuming, it influenced the quality of the data and the fairly high per-centage rate of completion.
2.3.1
organizationalinnovationOrganizational innovation represents a new method in the firm’s business practic-es, workplace organization or external relations that have not been previously used by the firm as a strategic decision.
34
ranked both in Albania and in the Adriatic Region. The biggest disparities in favour of Albania, compared to the Adriatic Region as a whole, are evident in the update of compensation policies. Furthermore, changes in the employees’ tasks, restructur-ing of intra-communications systems and alterrestructur-ing the ways in which the objectives are set, have the lowest ranking in both Albania and the Adriatic Region.
Chart 2.1 – Organizational innovation
(Albania in comparison to the Adriatic Region average)
4,45
4,78
4,07
4,60
4,53
4,27
4,09
4,65
3,83
5,22
4,29
4,84
4,31
4,13
3,80
4,13
4,01
4,62
4,05
4,70
-
1,00
2,00
3,00
4,00
5,00
6,00
Organizational Innovation (mean)
Renewal of internal rules and procedures
Changes in our employees’ tasks
New management systems implementation
Update of compensation policies
Restructuring of intra-communications system
Updating of organizational structure
Different roles within the organization
We usually alter the way in which we set objectives
Developing the structure effectiveness
Albania
Adriatic region
Albania4,45
4,78
4,07
4,60
4,53
4,27
4,09
4,65
3,83
5,22
4,29
4,84
4,31
4,13
3,80
4,13
4,01
4,62
4,05
4,70
-
1,00
2,00
3,00
4,00
5,00
6,00
Organizational Innovation (mean)
Renewal of internal rules and procedures
Changes in our employees’ tasks
New management systems implementation
Update of compensation policies
Restructuring of intra-communications system
Updating of organizational structure
Different roles within the organization
We usually alter the way in which we set objectives
Developing the structure effectiveness
Albania
Adriatic region
Adriatic Region2.3.2
internationalizationlevelasinnovationenabler35
2. ALBANIA
countries, Adriatic Region countries (47.17%), Western and Central Europe (27.36%) and Eastern Europe (18.87%).
As demonstrated in Chart 2.2 , in both cases, the least represented markets are those in South and Central America, North Africa, the Middle East, East Asia and North America. The national markets are the most represented areas in both Al-bania and the Adriatic Region as a whole; whereby in AlAl-bania, 78% of respondents were present on the domestic market, while for the Adriatic Region as a whole this rate amounts to 95%. The next most prevalent markets where companies sold their goods and services were in both cases those of the Adriatic Region countries, for 47% of companies operating in Albania and 31% in the Adriatic Region. In total, Adriatic countries have more intensive trade collaborations with Western, Central and Eastern Europe when compared with Albania, which remains a relatively more isolated country.
Chart 2.2 – Geographic markets where enterprises sold goods and/or services during 2011, 2012 and 2013
(Albania in comparison to the Adriatic Region average)
4,45
4,78
4,07
4,60
4,53
4,27
4,09
4,65
3,83
5,22
4,29
4,84
4,31
4,13
3,80
4,13
4,01
4,62
4,05
4,70
-
1,00
2,00
3,00
4,00
5,00
6,00
Organizational Innovation (mean)
Renewal of internal rules and procedures
Changes in our employees’ tasks
New management systems implementation
Update of compensation policies
Restructuring of intra-communications system
Updating of organizational structure
Different roles within the organization
We usually alter the way in which we set objectives
Developing the structure effectiveness
Albania
Adriatic region
Albania4,45
4,78
4,07
4,60
4,53
4,27
4,09
4,65
3,83
5,22
4,29
4,84
4,31
4,13
3,80
4,13
4,01
4,62
4,05
4,70
-
1,00
2,00
3,00
4,00
5,00
6,00
Organizational Innovation (mean)
Renewal of internal rules and procedures
Changes in our employees’ tasks
New management systems implementation
Update of compensation policies
Restructuring of intra-communications system
Updating of organizational structure
Different roles within the organization
We usually alter the way in which we set objectives
Developing the structure effectiveness
36
2.3.3
innovationincentivesasinnovationenablersPublic financial support of innovation activities remains low in the country. Central government is reported as the main public funding source for research and develop-ment by 10,5% of respondents. Local or regional authorities are stronger supporters in financing innovation in the Adriatic Region, in comparison with Albania where research and innovation is considered a national strategy. There are low levels of EU funding of innovation in Albania (5,95%), which might be explained by Albania’s delayed EU candidate status (June 2013) and the lack of capacities of Albanian com-panies to apply for EU funds under the stabilisation and association agreement.
As we can see in Chart 2.3 , the level of received support from local or regional authorities, as well as the EU, is low in Albania. Support received from the central government in Albania is slightly higher than the Adriatic Region average, although the overall public financial support in both cases (Albania and the Adriatic Region) is rather poor.
Chart 2.3 – Public financial support (%) for the innovation activities in enterprises during 2011, 2012 and 2013 coming from the government
(Albania in comparison to the Adriatic Region average)
4,45
4,78
4,07
4,60
4,53
4,27
4,09
4,65
3,83
5,22
4,29
4,84
4,31
4,13
3,80
4,13
4,01
4,62
4,05
4,70
-
1,00
2,00
3,00
4,00
5,00
6,00
Organizational Innovation (mean)
Renewal of internal rules and procedures
Changes in our employees’ tasks
New management systems implementation
Update of compensation policies
Restructuring of intra-communications system
Updating of organizational structure
Different roles within the organization
We usually alter the way in which we set objectives
Developing the structure effectiveness
Albania
Adriatic region
Albania4,45
4,78
4,07
4,60
4,53
4,27
4,09
4,65
3,83
5,22
4,29
4,84
4,31
4,13
3,80
4,13
4,01
4,62
4,05
4,70
-
1,00
2,00
3,00
4,00
5,00
6,00
Organizational Innovation (mean)
Renewal of internal rules and procedures
Changes in our employees’ tasks
New management systems implementation
Update of compensation policies
Restructuring of intra-communications system
Updating of organizational structure
Different roles within the organization
We usually alter the way in which we set objectives
Developing the structure effectiveness
37
2. ALBANIA
2.4 micro foundations of innovation
In Albania, three innovative, small-medium sized companies participated in the study. In total, 99 employees of the three companies were involved and completed the questionnaires. The first company was an internet service provider operating in Albania offering also digital cable television and telephone to its customers. It is the first service provider that has implemented digital technology in Albania and is innovative in providing services of high digital quality, based on the latest technolo-gies such as cable, optical fibre, ADSL, ADLS 2+, wireless, phone cards, etc. The sec-ond company was stable, with more than 15 years of experience in the retail chain of high-tech and innovative products in Albania and the Balkan Region. The third com-pany, operating in the furniture industry for over ten years, was well known for its innovative products designed mostly for the European market, but not exclusively.
The gender structure in three Albanian companies is almost balanced, with a representative of 52% male versus 48% female. The average employee age in the three Albanian companies is 30,6, which represents the lowest average employ-ee age on the level of the Adriatic Region. The percentage of employemploy-ees holding a Bachelor’s Degree (54,5%) represents the majority of the employees in the three Albanian companies involved in this survey, followed by the employees with com-pleted Master’s Degree (34,3%) and, finally, 10,1% of the employees that hold the high school diploma.
The following graph presents the average descriptive results for Albania in com-parison with the Adriatic Region. Furthermore, we are referring to the results of multi-level analysis at the Adriatic level.
The data show that knowledge hiding in Albania is not a common occurrence, as it stands at the level of 1,84, which is lower than the average of the Adriatic Re-gion (2,31). Interestingly, the econometric data analysis on the Adriatic ReRe-gion lev-el showed a slightly positive corrlev-elation between knowledge hiding and individual innovativeness, which is contradictory to the previous empirical studies that claim that knowledge hiding negatively affects innovativeness.
Employee silence construct is connected to the fact that the employees do not share their ideas openly and it stands at the level of 2,07 in Albania, which is slightly lower when compared to the Adriatic Region (2,71).
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The perceived time pressure determinant does not show any significant statis-tical correlation with the level of innovativeness in the surveyed companies of the Adriatic Region. On the basis of the survey carried out in Albania, this determinant is 3,68, while the Adriatic Region average is 4,12.
Creativity, idea championing and individual innovation are ranked at the high-est level in Albania (5,12) compared to other countries of the Adriatic Region, with the average value of 4,66.
Task conflict, as a measurement of disagreement between group members is presented at the level of 3,56 in Albania, while the average representation in the Adriatic Region stands at 3,24.
Absorption/flow at work, work enjoyment and intrinsic work motivation are ranked rather high in Albania (absorption= 4,54, work enjoyment=4,98, intrinsic work motivation=4,90), which is equal or slightly higher than the Adriatic Region average. However, the research has shown no significant correlation of these con-structs and individual-level innovativeness on the Adriatic Region level.
Chart 2.4 – Micro-determinants of innovation in Albania and the Adriatic Region
4,45
4,78
4,07
4,60
4,53
4,27
4,09
4,65
3,83
5,22
4,29
4,84
4,31
4,13
3,80
4,13
4,01
4,62
4,05
4,70
-
1,00
2,00
3,00
4,00
5,00
6,00
Organizational Innovation (mean)
Renewal of internal rules and procedures
Changes in our employees’ tasks
New management systems implementation
Update of compensation policies
Restructuring of intra-communications system
Updating of organizational structure
Different roles within the organization
We usually alter the way in which we set objectives
Developing the structure effectiveness
Albania
Adriatic region
Albania4,45
4,78
4,07
4,60
4,53
4,27
4,09
4,65
3,83
5,22
4,29
4,84
4,31
4,13
3,80
4,13
4,01
4,62
4,05
4,70
-
1,00
2,00
3,00
4,00
5,00
6,00
Organizational Innovation (mean)
Renewal of internal rules and procedures
Changes in our employees’ tasks
New management systems implementation
Update of compensation policies
Restructuring of intra-communications system
Updating of organizational structure
Different roles within the organization
We usually alter the way in which we set objectives
Developing the structure effectiveness
39
2. ALBANIA
When it comes to the time perspectives, the research data produced at the level of Adriatic Region show that only past positive and present hedonistic per-spectives are significantly related to innovativeness. Past negative and future time perspectives do not show significant influence at the Regional level. Interestingly, research has shown that in the countries of the Adriatic Region, past positive time perspectives, such as feeling pleasure when thinking about the past and nostalgia, are strongly negatively related with innovativeness. This suggests that the more dominant the past positive time perspectives in the employee, the less innovative the employee is. Past positive time perspectives is negatively correlated with in-novativeness at the Regional level, and it is almost equally ranked in both Albania (3,46), and the Adriatic Region (3,62), while present hedonistic time perspective is marginally positive correlated to innovativeness, and it is ranked higher in the case of Albania (3,74) compared to the average of the Adriatic Region (3,52). Past nega-tive and future time perspecnega-tives did not show any significant correlation with in-novativeness in the Region. Since in both cases, past negative time perspectives in Albania is ranked rather low, it may be interpreted as a positive result, while future time prospective is mid-ranked in Albania as well as the Adriatic Region.
Referring to time management, the survey carried out in the Adriatic Region shows some supporting evidence, while other variables turn out to be non-signifi-cant. First of all, it is confirmed that time management is positively and significant-ly correlated with the individual level innovativeness. It also represents one of the largest determinants of individual-level innovation (coefficient-wise). This determi-nant is ranked significantly high in Albania (5,36), which is slightly higher than the Adriatic Region average (5,1).
According to our research, entrepreneurial and intrapreneurial intentions are shown to be significantly related with employees’ innovativeness at the level of the Adriatic Region, which implies that entrepreneurial skills may be of potential benefit for the company as it stimulates the innovation processes. This determi-nant in Albania stands at the level of 4,99, which is higher than the Adriatic Region average (4,03).
Self-efficacy, which has been identified as an inhibitor of innovativeness in this research on the Adriatic Region countries, is ranked rather high (5,63). This could point to the conclusion that employees in Albanian companies are more optimistic regarding their abilities to perform new tasks.
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Individualism, as another construct that measures national culture, represents a rank of 5,55 in Albania and 4,48 in the Adriatic Region. The same as in case of un-certainty avoidance, the econometric analysis showed that this determinant does not play a significant role in explaining the individual-level innovativeness in the Adriatic Region.
2.5 conclusions
41
2. ALBANIA
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1. Institute of Statistics of Albania (INSTAT). (2011). Main Findings.
2. European Commission. EU candidate status for Albania. (2014). Retrieved from http://europa.eu/rapid/press-release_MEMO-14-439_en.htm
3. Albanian Investment Development Agency Report. (2015). Retrieved from http://www.aida.gov.al/home.
4. World Economic Forum. (2014-2015). The Global Competitiveness Report. Re-trieved from http://www3.weforum.org/docs/WEF_GlobalCompetitivenessRe-port_2014-15.pdf
5. UNDP. (2014). Human Development Report. Retrieved from
http://hdr.undp.org/en/content/human-development-report-2014 6. Institute of Statistics of Albania (INSTAT). (2014a). Labor Market, 2014. Retrieved from http://www.instat.gov.al/media/291851/tregu_i_pun_s_2014.pdf.
7. Ministry of European Integration. (2015). Retrieved from http://www.integrimi.gov.al 8. Miluka, J. (2011). Gender wage gap in Albania: Sources and recommendations.
Pegi Tirana, Albania: UN Women.
9. Institute of Statistics of Albania (INSTAT). (2014b). Women and men in Albania 2014. Retrieved from http://www.instat.gov.al/media/257796/femra_dhe_ meshkuj_2014_.pdf.
10. Institute of Statistics of Albania (INSTAT). (2015). Youth in Albania: Challenges in changing times. Retrieved from http://www.instat.gov.al/media/316725/ youth_in_albania_challenges_in_changing_times.pdf.
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BOSNIA AND HERZE
GO
VINA
ARSLANAGIĆ-KALAJDŽIĆ, MAJA; TURULJA, LEJLA
School of Economic and Business (SEBS), University of Sarajevo
Chapter 3
Bosnia and Herzegovina
highlights
• Bosnia and Herzegovina (B&H) is a South-Eastern European country, situated in the heart of Balkans.
• Due to the destructive war in the 1990s, and the dysfunctional structure of the country that resulted from the Dayton agreement, Bosnia and Herzegovina is lagging behind oth-er countries in the region.
• The GDP per capita of B&H places the country far below the average of the Adriatic Re-gion, as well as below the EU-28 average.
• In comparison to the Regional and EU-28 mean, B&H has a far lower number of new PhD graduates, in relative terms.
• B&H SMEs show relatively poor levels of internationalisation, where national markets are the most represented areas with the presence of 98%.
• The level of received support through innovation incentives from the government, Re-gional authorities and the EU is low for all measured forms of financing. The majority of innovative firms in B&H within the three-year period 2011-2013 did not receive any kind of public financial support for innovative activities.
