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Dynamic capabilities view based competitive advantage, country competitiveness and
manifestation of entrepreneurship research methodology
Asta Pundzienė, Kaunas University of Technology, Lithuanian, Solveiga Buožiūtė-Rafanavičienė, Kaunas
University of Technology, Lithuanian, Evelina Meilienė, Kaunas University of Technology, Lithuanian, Sigita
Neverauskaitė, Kaunas University of Technology, Lithuanian, Lolita Jurksiene, Kaunas University of
Technology, Lithuanian, Jurgita Giniuniene, Kaunas University of Technology, Lithuanian, Monika Petraite,
Kaunas University of Technology, Lithuanian, Petras Barsauskas, Kaunas University of Technology,
Lithuanian, Ruta Aidis, George Mason University, USA
Key works: dynamic capabilities view, entrepreneurship, competitive advantage, innovations, corporate
entrepreneurship, and innovative technological firms
Introduction
Permanent search for the explanation of the competitive advantage makes scholars to constantly rethink
paradigm theories, views as well as theoretical perspectives. Resource-based view is no longer sufficiently
explaining competitive advantage of the firms in the innovation economy. Thus, new perspective should be
developed. Prahalad (1990), Minzberg et al. (2003) and others offered dynamic capabilities as the new
perspective that should explain processes that take place in the firm in order to match the dynamic, volatile
environment. Many scholars (Teece, Hefalt, Eisenhardt, Winter and etc.) made efforts to operationalise
dynamic capabilities however the main challenge was to eliminate the overlap between dynamic
capabilities and akin concepts - corporate entrepreneurship, entrepreneurship, innovations, learning and
knowledge management as well as change management. This paper aims to elaborate dynamic capabilities
view and its relationship with country competiveness and the level of entrepreneurship. The aim is
ambitious, however helps to solve several challenges – to develop taxonomy that set clear relationships
between akin concepts and sort out far-gone confusion; to develop empirical research methodology for
testing the model.
Conceptualisation and operationalization of the Dynamic capabilities view
The authors of this paper suggest an entirely novel approach to understanding the relationship between
dynamic capabilities, corporate entrepreneurship, innovation management, organisation learning and
knowledge management as well as change management. The authors argue that dynamic capabilities can
be seen as paradigm embracing corporate entrepreneurship, innovations, organizational learning,
knowledge management, change management, and possibly further disciplines (Picture 1).
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Picture 1. Coverage of the Dynamic capabilities view
The emergence of the dynamic capabilities concept and related theory has been hindered by the lack of an
adequate explanation for how and why some firms develop competitive advantage in rapidly changing
environments (Eisenhardt and Martin, 2000) while others do not. However, scholars elaborating on Teece’s
position identified dynamic capabilities as a distinct function and attempted to construct a framework of
indicators to measure the phenomenon and its impact on a variety of variables, such as corporate
entrepreneurship, innovations, knowledge management, and change management. As the literature
analysis reveals, a clear overlap with the established theories of corporate entrepreneurship, innovations,
etc, is in evidence. Of course, difficulties also arose attempting to empirically measure the phenomenon
and its relationship with other variables. As Arend and Bromiley (2009) state, a dynamic capabilities
perspective offers an incomplete theory, oversimplifying a complex phenomenon and not clearly defining
its domain of relevance. The presently proposed assumption and conceptual model of the dynamic
capabilities paradigm offers explanation as to why and how some companies achieve competitive
advantage in a volatile, changing environment (Picture 2).
Corporate entrepreneurship
Change management
Innovation management
Learning loops and knowledge management
Volatile
environment;
Country
competitive
advantage in
innovation
economy
Environment
scanning, new
information
Opportunity
search and
exploration
New agenda
and setting
change project
Opportunity
exploitation and
reconfiguration
New knowledge
and innovation
Dynamic
capabilities
based firm’s
Competitive
advantage
Underlying log frame: Sensing on the level of resources and capabilities – processing new data – innovating – learning – upgrading resources and capabilities – sensing on new level - new cycle
Strategic management knowledge domain/ Competitive advantage
Dynamic capabilities view (Final list of the constituting disciplines should be tested empirically)
Resource-based
view
Corporate entrepreneurship discipline
Innovation management discipline
Organizational learning & knowledge management discipline
Change management discipline
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Picture 2. Dynamic capabilities view based competitive advantage in relation to country competitiveness
conceptual model
According to this approach, the emergence of dynamic capabilities view was basically conditioned by the
deficiency of the resource-based as well as action based views (Mintzberg et al., 2003) under the conditions
of the economy of innovation.
Corporate entrepreneurship
Corporate entrepreneurial behavior (also referred to in the literature as corporate venturing or
intrapreneurship) serves for organizations for purposes of financial gains (Zahra, 1991), strategic renewal
(Guth and Ginsberg, 1990), gaining knowledge (McGrath, Venkataraman, and MacMillan, 1994),
innovativeness (Baden-Fuller, 1995), and internationalization (Birkinshaw, 1997).
The concept of corporate entrepreneurship has been evolving over the last twenty-five years. Researchers
have conceptualized corporate entrepreneurship as a process of organizational renewal (Sathe, 1985) or
entrepreneurial efforts that require organizational sanctions and resource commitments for the purpose of
carrying out innovative activities in the form of product, process, and organizational innovations (Jennings
and Young, 1990). Guth and Ginsberg (1990) stressed that corporate entrepreneurship encompasses two
major types of phenomena: new venture creation within existing organizations and the transformation of
organizations through strategic renewal.
As stated by Scheepers et al. (2008), entrepreneurship can result in a new product, service, process, or
business development. Entrepreneurship may be chosen as a strategy in order to increase financial
performance, though it also leads to non-financial benefits, such as increased employee morale,
collaboration, and a creative working environment (Hayton, 2005).
Many authors subscribe to the view that firm-level entrepreneurial orientation serves as an indicator of
corporate entrepreneurship capability. Firm-level entrepreneurial orientation is reflected by three
dimensions: innovativeness, proactiveness, and risk-taking (Zahra, 1991). However, some authors, such as
Lumpkin and Dess (1996), argue that five dimensions, rather than three, should be used to capture
entrepreneurial orientation – namely: autonomy, competitive aggressiveness, pro-activeness,
innovativeness, and risk-taking.
Ahmad and Seymour (2008) understand entrepreneurial activity through four key aspects: (a) enterprising
human activity; (b) the assembly of unique bundles of resources, identification of market opportunities,
and/or utilisation of innovative capabilities; (c) the significance of the business and wider environments;
and (d) the creation of value.
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Entrepreneurial capability is also seen as a means of capturing a firm’s capacity to sense, select, shape, and
synchronize its pursuit of opportunities (Zahra et al., 2006).
Corporate entrepreneurship refers to the set of activities companies and their members undertake to enter
new market arenas which offer opportunities for growth and profit. It usually refers to the level of
organizations and often concerns top-down processes and management strategies (De Jong and
Wennekers, 2008). According to several authors (Guth and Ginsberg, 1990; Sharma and Chrisman, 1999;
Covin and Miles, 2007), corporate entrepreneurship includes corporate venturing and strategic renewal,
where corporate venturing is related to the generation of new business initiatives and corporate renewal
involves redefining the mission of the company, the construction of a new business model, the
reformulation of competitive strategic bases, and the acquisition or generation of new skills.
The knowledge domain of corporate entrepreneurship is expanding vastly, however the existing knowledge
frameworks do not provide an adequate structured framework to eliminate the elusiveness of the
phenomenon.
Researchers of corporate entrepreneurship and dynamic capabilities discuss these phenomena using
different terms, though often they are employing very similar meanings. Teece (2007) describes dynamic
capabilities as three ingredients: sensing new opportunities, seizing and reconfiguration. The recognition,
evaluation, and exploitation of opportunities are core concepts in the study of entrepreneurship (Alvarez
and Barney, 2007).
For the purpose of the analysis, the authors of this paper have chosen Teece’s (2007) definition of dynamic
capabilities, and consider overlaps through the lenses of various theories of corporate entrepreneurship
and dynamic capabilities.
Theories of corporate entrepreneurship emphasize the importance of entrepreneurial opportunities,
focusing on opportunity seeking and creation. Even though disagreements exist around what constitutes an
opportunity, it is essentially related to the possibility to meet market needs through a creative combination
of resources to deliver value to stakeholders. As Audretsch (1995) and Adner and Levinthal (2001) state,
these opportunities arise from market conditions and company capabilities, resources, and skills.
Opportunity seeking is described as entrepreneurial interest in exploring the environment without being
limited to official definitions of business domains and which is triggered by challenges faced by the
company (Rosenkopf and Nerkar, 2001). Zahra (2009) proposes that opportunity seeking is an essential and
integral part of the definition of entrepreneurial opportunities, where passive seeking is related to
discovery and proactive seeking is central to the creation theory. According to Zahra (2009), the process of
seeking differs in scope, duration, novelty, participants, goals, and knowledge. An entrepreneur’s
perception, cognition, definition, and recognition of opportunities is significantly influenced by the
differences between these attributes. According to researchers, opportunity recognition is a process
involving scanning and sensing the environment, identifying gaps in market need, comparing gaps and
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available resources, and developing the mechanisms by which gaps are filled (Alvarez and Barney, 2007;
Ardichvili, Cardozo, Ray, 2003).
Another concept addressed in the literature on entrepreneurship is alertness. According to Shane (2000),
alertness usually revolves around market needs, ways of serving customers, and ways of addressing
particular customer problems, and increases the entrepreneur’s alertness to potential opportunities.
Research on corporate entrepreneurship emphasizes that the creation of opportunities requires more than
the mere recognition of existing opportunities; it requires sensing, developing, evaluating, and reframing
opportunities (O’Connor and Rice, 2001). According to research findings, the discovery and creation of
opportunities depends on the organizational goals and structures, corporate cultures and networks, and
the political and aspirational climate of the company (Alvarez and Barney, 2007).
The term ‘opportunity identification’ is used in the literature when emphasizing technical skills such as
financial analysis and market research, as well as creativity, team building, problem solving, and leadership
(Long and McMullan, 1984; Hills, Lumpkin, and Singh, 1997; Hindle, 2004). As summarized by Shane (2003:
4–5), entrepreneurship ‘is an activity that involves the discovery, evaluation, and exploitation of
opportunities to introduce new goods and services, ways of organizing markets, process, and raw materials
through organizing efforts that previously had not existed’.
Innovation management
Innovation management metrics reflect the basic changes within innovation theory and shift from linear
innovation model towards open innovation models, providing much larger varieties of organizing for
innovation and benefiting from them. As suggested by study of Milbergs, Vonortas (2007), four generations
of innovation metrics could be distinguished, which are classified around innovation inputs, outputs,
comparative elements, and innovation processes (Washington, 2007) at the macro level. The first
generation innovation metrics (developed in 1950s – 60s) extensively relied on the linear innovation model,
where innovation would be considered as a result of supply based factors, such as R&D expenditures, S&T
personnel, capital and technology intensity (i.e. technology investments from the industry). As a result,
organizations were merely measuring not the innovation performance but innovation inputs with having
little control on return on investment in innovation, nor organizational processes. The second generation of
innovation metrics (developed in 1970- 80s), which was based extensively on innovation outputs, thus
allowing the organizations to link inputs with the outputs. Typical innovation output based indicators would
be patents, publications, new products and quality change. Entire group of indicators allows organizations
to control innovation performance as based on the market returns, however no impact on innovation
performance as a competitive and strategis activity. The rise of benchmarking based indicators to measure
organizational performance (Kaplan, Norton, 1996) impacted the formation of third generation of
innovation indicators, which followed benchmarking model, and was exceptionally based on innovation
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surveys, benchmarking, innovation indexes and capacity comparative measurements back in 1990. Entire
period was also marked with the development of innovation measurement indicator systems to support
theory of national innovation systems (Dosi, 1988, Lundvall, 1992) at the macro level and corporate
scoreboard and benchmarking systems at the organizational level, which had laid the ground for
comprehensive analyse of innovation performance by firms and economies. Though changing innovation
models and development of organization theory has turned the attention towards organizational processes
for innovation, as being fundamentals for both, maximising returns from innovation inputs, and
competitive outputs. The indicators changed from quantitative to qualitative, and embraced such processes
and resources, as knowledge, intangibles, networks, demand and customer participation, clusters,
management techniques, risk and return indicators, and system dynamics. Entire trend as formed in 2000
continues and aims at establishment of comprehensive innovation measurement systems at the
organizational and upper levels of social organizing for innovation.
Indicators presented below support innovation process measurement across the major innovation stages
(ideation and conceptualization stage, feasibility and capability building, commercialization). Innovation
measurement criteria at the organizational level could be organized around economic and firm
performance metrics (innovation input and output indictors, return on investment and etc.), innovation
process metrics (Gopalakrishnan and Damanpour, 1997, Crossan, Apaydin, 2010), organizational
capabilities for innovation (defined as managerial levers by Crossan, Apaydin, 2010) and strategy and
leadership based indicators (Kaplan, Winby, 2007, Palmer, Kaplan (2007)
Economic and innovation performance metrics (innovation input and output indictors, return on
investment and etc.), could be classified along inputs, outputs and performance based indicators. Input
indicators would encompass R&D intensity (absolute and relative, as an annual R&D budget as a
percentage of annual sales) (Parthasarthy and Hammond, 2002), total R&D personnel or budget as a
percentage of sales (Kaplan, Winby, 2007); investment in gathering ideas from outside (Kaplan, Winby,
2007); commitment to differentiated funding for innovation (White, 2002). But also investments in
capabilities would be important such as investment in innovation process and learning, share of employees
who have received training and tools for innovation, instruction in estimating market potential of an idea
(Kaplan, Winby, 2007), and also capability building input indicators, such as share of capital invested in
innovation activities such as submitting and reviewing ideas for new products and services and developing
ideas through an innovation pipeline; Percentage of “outside” vs. “inside” inputs to the innovation process
(open innovation); (Kaplan, Winby, 2007);
Output based indicators would encompass: knowledge based indicators, such as total number of patents
and number of patents filed in the past year, number of publications; market based indicators, such as new
products to existing market, number of new products, services, and businesses launched in new markets in
the past year (Kaplan, Winby, 2007); share of revenue/profit from products or services introduced in the
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past X years; Royalty and licensing income from patents and other intellectual property (Kaplan, Winby,
2007);
Innovation performance based indicators would focus on return of investment to innovation (ROI), Quality
change, actual vs. targeted breakeven time (BET); number of innovations that significantly advance existing
businesses; number of new-to-company opportunities in new markets
Innovation process metrics would be built around innovation stage gates and encompass ideation stage
indicators, feasibility and capability based indicators and also commercialisation stage based indicators.
Ideation stage measurement parameters would be linked to process management capabilities: ideation
and recognition of need for innovation (Gopalakrishnan, Damanpour, 1997, Ettlie, 1980, Harvey and Mills,
1970), concept generation and decision about undertaking innovation and ways to achieve it (adoption vs
generation (Chiesa et al, 1996); number of ideas submitted by employees (Kaplan, Winby, 2007); focus for
initiatives geared toward building repeatable and sustainable approaches to invention and re-invention
(Kaplan, Winby, 2007); extent of usage of formal idea generation and support tools (Cebon and Newton,
1999, Loch et al, 1996); to economic and firm performance indicators, such as risk and return balance (ROI)
(Bard et al, 1988), constrained optimization to maximize output (Schmidt, Feeland, 1992), economic and
benefit models applied by firm (Hall, Nauda, 1990), firm performance indicators: using formalized
optimization tools (Cooper et al, 1999, 2001), using formalized process of project selection (Cebon,
Newton, 1999, etc.), Project selection efficiency (Szakony, 1994), post-hoc project results (Lee et al, 1996).
Feasibility and development stage measurement indicators should embrace process management
capabilities, such as adoption of innovation (Rogers, 1993; Wolfe, 1994), generation and development of
innovation (Saren, 1984, Wolfe, 1994), implementation (production) (Zaltman et al, 1973), project
management capabilities, such as formal innovation project management tolls, i.e. problem finding solving
cycle (Bessant, 2003, certified processes, Chiesa et al, 1996), project efficiency (actual budget, cost,
revenues), Innovation speed (Hauser and Zettlemeyer, 1997, Elwood, Grimshaw, Pandra 2013, innovation
schedule (Chiesa and Masella, 1994), duration (Cebon and Newton, 1999); communication and
collaboration in innovation process, such as internal and external communication (Damanpour, 1991,
Cebon and Newton, 1999), collaboration with suppliers, customers, strategic partners (Bessant, 2003, von
Hippel, 1986), team (Jassawalia and Sashittal, 1999).
Commercialization (launch and post launch) stage indicators should encompass market feasibility building
and monitoring (Verhaeghe and Kfir, 2002), budget and commitment to market testing and launch
(Balachandra and Blockhoff, 1995), share of new product launches per year (Yoon, Lilien, 1985), launch
proficiency; post launch reviews (Atuahene – Gima, 1995), adherence to launch and sales Schedule (Griffin
and Page, 1993).
The innovation process metrics should be also complemented with crosscutting innovation process
management parameters, that would include knowledge management (knowledge sources for innovation,
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variety and change of networks at initiation, development and commercialisation stages), networks
(Milbergs, Vonortas, 2006), management techniques for innovation (Adams et al, 2007).
Organizational capabilities for innovation indicators would group a large separate group of inidcators, that
would to a large extent explain organizational innovation process and related input and output
performance. The organizational capabilities indicators are linked to organizational learning and knowledge
management, such as number of new competencies (distinctive skills and knowledge domains that spawn
innovation (Kaplan, Winby, 2007), support for experimentation (Damanapour, 1991, King et al, 1992),
tolerance of failed ideas (Madjar et al, 2002), adoption of risk taking norms (King et al, 1992, West and
Anderson, 1992); organizational capability metrics (structure and systems for innovation), such as
specialization, formalization, organization complexity, administrative intensity (Damanapour, 1991, West
et al, 1998, Admas et al, 2006); existence of formal structures and processes that support innovation
(Kaplan, Winby, 2007). The universal empirically retrieved organizational characteristics constituting
organizational capabilities for innovation (Petraite et al, 2012) embrace organizational structure related
determinants: flexible and initiative supporting organizational procedures; distributed decision making
rights; clear allocation of innovation tasks; competence and project based dynamic organizational structure
as an opposite to strictly regulated organizational structure; organizational infrastructure related
determinants: participation (of users and employees) facilitating IT platform; effective and flexible
information and innovation experience management system; creativity and cooperation facilitating physical
organizational infrastructure; Innovation partnership supporting IT and physical infrastructure; organization
and monitoring of innovation activities: Effective management of innovation processes, effective system of
innovation activity monitoring and results measurement, effective and precise innovation management
decision making; organizational culture in relation to innovation: organizational climate supporting diversity
of ideas and opinions, value based orientation towards innovation, high tolerance of innovation risks;
organizational communication: effective system of innovation activity communication; knowledge and
learning processes for innovation: R&D knowledge development for innovation, individual and group based
innovation competence development, learning for innovation supporting organizational systems,
absorption of internal and external innovation experiences, enabling learning results for innovation,
development of strategic innovation competencies internally, external sourcing for innovation ideas,
support to creativity for innovation, internal experience based learning for innovation, routine based and
customer oriented organizational learning; organizational support for innovation: concentration and
direction of human resources towards innovation activity, innovation supporting motivation and career
system; and management profile for innovation: distinction of innovation as a management field,
competence based dynamic management as an opposite to formal fixed management, professional
management of innovation.
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Strategy and leadership based indicators (Kaplan, Winby, 2007), Palmer, Kaplan (2007), Adams et al, 2006)
should encompass innovation strategy: explicit, with adequate resource acquisition and allocation at the
strategic planning level (Petraite et al, 2012); mission, goals and strategy alignment (innovation goals match
strategic objectives, Tipping, Zefren, 1995), general strategy: System dynamics, Risk/return indicators
(Milbergs, Vorontas, 2006), explicitness of Innovation Strategy (Miller, Friesen, 1982), leadership: share of
executives’ time spent on strategic innovation versus day-to-day operations; Share of managers with
training in the concepts and tools of innovation; Share of product/service or strategic innovation projects
with assigned executive sponsors; number of managers that become leaders of new category businesses
and organizational capabilities for innovation metrics itself, and also strategy and leadership level metrics
(Kaplan, Winby, 2007).
Learning, knowledge management
As a final factor, affecting corporate entrepreneurial action within the enterprise might be found
organizational learning process. The constant need for change and flexibility within entrepreneurial
organization creates an organizational learning and knowledge acquisition, transformation context (Burns,
2005). At the start-up phase entrepreneur learns quickly, and transfers learning and knowledge fast,
without communication barriers. However, once organization grows it becomes challenging for corporate
entrepreneur to keep the fast pace of learning activities across organization. At this phase learning
organization’s concept must be incorporated into corporate strategy. Pedler et al. (1991) defined learning
organization as the organization that creates the abilities to its team members to continuously learn by
adapting, changing, developing and transforming themselves in response to the changes in the external
environment. The response to the changes in the external business environment is one of the primary
focuses in the entrepreneurial organization. Therefore, the entrepreneurial organization that is a learning
organization encourages systematic problem solving processes across organization; encourages
experimentation and new approaches; learns from the past and best practices; is skilled at transferring
knowledge within organization (Burns, 2005). Senge (1992) and Timmons (1999) argue that learning
organizations might be only built by leaders who are the learners and the teachers at the same time.
Therefore, organization is truly entrepreneurial when it is a learning organization as well.
According to Kim (1993) during the first half of the cycle individual test the concepts and observe through
experience – “know-how” learning phase. During the second half of cycle the learner reflects on what he
observed and forms new concepts – “know-why” learning phase. Such learning is also called “double-loop”
learning.
Double-loop learning occurs when organization in order to respond to the changes in the environment
modifies the underlying model that guides its actions (Sadler-Smith, 2006). According to Argyris and Schon
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(1996) change in organization’s norms, values and objectives must happen because its usual methods for
errors correction are not sufficient.
Double-loop learning and especially “know-why” learning phase is highly important to entrepreneurial
organization because it captures the roots of the problems and enable systematic solutions to be put in
place.
Originally the learning loop model was first introduced by Argyris and Schon (1996) in the organizational
learning theory. Researchers distinguish between two different levels of organizational learning: single-loop
learning and double-loop learning (Picture 3).
Single-loop learning
Double-loop learning
Picture 3. Single-loop and double loop learning (Sadler-Smith, 2006)
Single-loop learning occurs when the organization deals with discontinuous changes in the external
environment without changing the assumptions and goals that guide organization‘s actions (Sadler-Smith,
2006). Single-loop learning allows error correction process by making changes to routine behaviour only
not to the current course of organization (Argyris and Schon, 1996). The only change that takes place within
organization during single-loop learning is the shift in the norms of the organization (Ambrosini et al.,
2009).
Assumptions and
goals
Organizational
actions
Organizational
outcomes
Correction of actions on
basis of error detection
Assumptions and
goals
Organizational
actions
Organizational
outcomes
Correction of actions on
basis of error detection Correction of assumptions
and goals on basis of error
detection
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Double-loop learning occurs when organization in order to respond to the changes in the environment
modifies the underlying model that guides its actions (Sadler-Smith, 2006). According to Argyris and Schon
(1996) change in organization’s norms, values and objectives must happen because it is usual methods for
errors correction are not sufficient.
Referring to Winter’s (2003) work, it might be seen that ordinary capabilities (second order dynamic
capabilities) might be associated to single-loop learning model because they are related to the changes to
the resource base of the organization but the actual way how these changes are performed does not
change. Higher order dynamic capabilities, on the other hand, are more related to double-loop learning
model as the changes that occur are transformational in nature.
Further analysis of the work done by scholars so far in the fields of corporate entrepreneurship and
dynamic capabilities suggests that double loop learning model may be easily adopted in order to illustrate
the overall relationship between the corporate entrepreneurship and dynamic capabilities.
Competitiveness and Competitive advantage
The complex measurement of regional/country’s competitiveness is becoming one of the most important
stages in strategic planning as well as presumption of the improvement of regional and national
competitiveness. The problems of the complex measurement of competitiveness within the region/country
are analysed in this case.
In the globalized world, the concept of the competitiveness has gained and has been gaining an
unprecedented importance in the recent years. Few fundamental studies intended to solve the problems of
competitiveness were prepared in the theoretical level of science. The theories and view of the most
famous authors (M. Porter, 1990, 2000, P. Krugman, 1994, 1996, A. M. Rugman and others, 1998, D. S. Cho,
1994, D. S. Cho, H. C. Moon, 1998, J. Reiljan and others, 2000, EC, 2001, 1999, B. Gardiner and others, 2004)
are mostly intended to analyse the competitiveness of national level. The authors do not bring to the fore
different ways of achieving of competitiveness for developed, developing or transitional countries however.
World’s scientific literature pays lot of attention to the researches of competitiveness. Some features of
industrial competitiveness could be found already in the studies of researchers of XVIII century (A.S mith, D.
Rikardo, Hecksher-Ohlin, P.A. Samuelson), where they studied the aspects of absolute ant relative
advantages of the countries.
The concept of competitiveness is one of the most sophisticated and hard summarized areas of the study.
This is determined by discussions on expedience of application of the concept of competitiveness to
countries (M. Porter, 1990, P. Krugman, 1994, R. Camagni, 2002, I. Turok, 2004), the width and versatility of
the concept, the absence of universally accepted description, plenty of factors of competitiveness and the
complexity of the ties between them. Scientific literature often brings to the fore one or few single factors
of competitiveness. Their systematic coupling to theoretical models of competitiveness of the country was
12
properly researched in the studies of M. Porter (1990), A. M. Rugman and others (1998), D. S. Cho, H. C.
Moon (1998), D. S. Cho (1994).
An analysis of different approaches to the concept of national competitiveness, possible to state that this
approach focuses on economic factors. As mentioned above, there is no pure competitiveness theory as
such, but different concepts trying to provide a framework for competitiveness (for an overview see e.g.,
Thomas B. Berger 2008, Budd and Hirmis 2004, Cellini and Soci 2002, Gersmeyer 2004, Kitson, Martin, and
Tyler 2004, Marniesse and Filipiak 2004, McFetridge 1995, Mitschke 2000, Lall 2001, Walter 2005). In the
following, broader concepts of competitiveness on the national level are presented, following the structure
of Trabold (1995). These four concepts discussed are the ability to sell, the ability to earn, the ability to
adjust, and the ability to attract (picture 4).
Picture 4. Hierarchy of national competitiveness (by H. Trabold)
Therefore, ability to earn considered as a general indicator of the competitiveness of the country and
abilities to sell, adjust and attract named as the country's competitiveness in describing factors.
Ability to Earn: Productivity and Performance Orientation
Supporters of this view start by looking at the “results” of an economy as this will indicate the level of
national competitiveness, i.e. it is assumed that a higher degree of competitiveness leads to a higher GDP
or income and therefore to a higher level of standards of living (Begg 1999, Budd and Hirmis 2004,
McFetridge 1995). The source for this is seen in productivity gains (Porter 1990).
Ability to Sell: Costs and Trade Performance
The ability to sell view treats nations like companies and asserts that nations are playing a zero-sum-game,
i.e. they compete internationally for market shares. “[A] country has become more or less competitive if, as
a result of cost-and-price developments or other factors, her ability to sell in foreign or domestic markets
has deteriorated or improved” (Balassa 1962) Two strands here can be distinguished: price based and non-
price-based competitiveness (Marniesse and Filipiak 2004, McFetridge 1995, Mitschke 2000).
Ability to Attract: Place Attractiveness
The ability to earn
Knowledge
The ability
to sell
The ability
to attract
The ability
to adjust
13
Supporters here view competitiveness as the possibility to attract outside investments such as financial
capital but also human capital. Kovacic (2007): “The economic prosperity of countries is associated with
their ability to generate or attract economic activities […]”.Hence, one of the most important single
indicators to assess place attractiveness for investments is the level of foreign direct investments (FDI)
(Gilmore et al 2003, Greene, Tracey, and Cowling 2007, Morgan 2004, Müller and Kornmeier 2000). They
assume that investors, when thinking about investing capital, will look for the best location to invest the
money and will choose the place which will yield the highest possible returns. The inflows of capital from
abroad therefore stand for competitiveness as the places with the highest possible returns will be more
competitive and therefore will attract more investments. When following this view, by looking at the
amount of FDI, one can assess the competitiveness of a country as this shows that investors are willing to
invest in this country and see opportunities for future profits.
Ability to Adjust: Innovation and Flexibility
"The fundamental impulse that sets and keeps the capitalist engine in motion comes from the new
consumers' goods, the new methods of production or transportation, the new markets, the new forms of
industrial organization that capitalist enterprise creates" (Schumpeter 1942, 831). Based on this famous
remark, the ability to adjust to changes in the environment is seen as being crucial for the competitiveness
of nations as a whole. Two different concepts here can be summarized: the ability to adjust political
procedures as well as the economic system as a whole (societal level) and the ability to adjust via
innovations and technological change (business level). These two go hand in hand as innovations will only
be meaningful and can only be applied, if a society is “open” to such changes, be it economically or in
general. This also stresses out the importance of free markets, open economies and entrepreneurship
(Magaziner and Reich 1982, Thurow 1992, Hospers 2006).
Generalizing different interpretations of competitiveness, authors present the relationship between the
competitiveness of different economic entities (see Figure 5). The competitiveness of an individual (who is
an employee of a company) is formed mainly by his education, abilities and motivation. The company uses
training programs and motivation systems to enhance the competitiveness of its employee and thus the
whole company (taking the abilities and skills of an employee as given). Combining these elements each
company develops the appropriate quality to price ratio that keeps the company competitive. From the
standpoint of an industry, besides the competitiveness arising directly from companies’ rationality of
expenditures (price to quality ratio) also other factors become important. Namely, the overall technical and
technological development in the industry as well as political-economic conditions the industry enjoys
(depends on its political power and lobby). Competitiveness of an industry is both determined by and also
revealed in the level of development of production in this industry. This in turn is part of the
competitiveness of the whole country, together with the economic and political position of the country in
the world economy and its infrastructural development.
14
Picture 5. Links between economic competitiveness of entities on different levels.
However, economic success of a country forms only the material basis for successful development of the
whole society and for raising the living standard of individual people. Besides economic dimension, great
importance has been attributed to social dimension.
Research methodology
Research design and methods
The empirical research has a complex aim to test the conceptual model as well as to develop Dynamic
capabilities index. For this we apply mixed – concurrent and transformative, where needed, research
strategy and design. Also research is conducted in several stages in order to have an opportunity to
supplement theory building and conceptual model testing with needed extra information gradually also to
have triangulated in depth insight into the phenomenon. In that way also issues of data validity as well as
reliability is handled. The research is based on positivistic and deductive research strategy, which means
that primary aim of first research stage was to make in depth literature analysis and to develop conceptual
model as well as set of the indicators that will be used to develop research model as well as research tools.
The second stage is devoted to case studies in order to test the theory and compliment if needed. The third
and fourth stages contribute to theory testing.
COMPETITIVNESS OF AN EMPLOYEE
EDUCATION MOTVATION
ABILITIES AND SKILLS OF EMPLOYEES
COMPETITIVENESS OF A COMPANY
RATIONALITY OF EXPENDITURES
MOTIVATION SYSTEM
TRAINING SYSTEM
LEVEL OF DEVELOPMENT OF PRODUCTION
TECHNICAL AND TECHNOLOGICAL DEVELOPMENT
POLITICAL –
ECONOMIC CONDITIONS
COMPETITIVENESS OF A INDUSTRY
ECONOMICAL AND POLITICAL POSITION
ECONOMIC COMPETITIVENESS OF A REGION
LEVEL OF DEVELOPMENT OF PRODUCTION
ECONOMIC COMPETITIVENESS OF A COUNTRY
INFRASTRUCTURAL DEVELOPMENT
ECONOMICAL POSITION OF A REGION
INFRASTRUCTURAL
DEVELOPMENT OF A REGION
Abilities
15
Table 1. Methods across research stages
Stage of the research Research design Aim
1 stage In depth research literature
and related indexes
analysis
To develop conceptual model as well as the frame
of the variables and indicators to be tested and
validated in the following stages
2 stage Case study To use for theory building as well as testing and to
validate survey scales
Experiment To use for conceptual model testing as well as
validating the theory build during case study
3 stage Survey To test the conceptual model and collect missing
data
4 stage Dynamic capability Index
construction
To develop an innovative instrument to measure
innovative technological firms adaptability to
volatile environment
All data collection instruments (interview and observation guide, document analysis, website, experiment
report as well as structured interview, etc.) are based on the three major scales and their indicators:
Country competitiveness
Dynamic capabilities
Firm competitive advantage
Table 2. Scales and indicators
Dynamic capabilities view indicators
Dimension Source Indicators (Interview, survey,
experiment)
Indicators
(secondary data)
Sensing
the ability to
identify
opportunities
and threats,
that requires
Sensing of
macroeconomic
factors
Teece
(2007)
Schilke
(2013)
a) The company was ready to
quickly react to the changing
external environment;
b) The company anticipate the
change of macroeconomic
situation;
c) We frequently scan the
16
the constant
surveillance
and
monitoring
across
markets and
technologies
(Teece et al.,
1997; Wang &
Ahmed,
2007).. It
relates not
only to the
capacity to
perceive
opportunities
in the
environment
but also on
the potential
of
organizations
to actively
shape their
environments
(Eisenhardt &
Martin, 2000;
Teece, 2007).
environment to identify new
business opportunities;
d) Company is effective in
developing new knowledge or
insights that have the
potential to influence product
development;
e) The environmental demands
on company are constantly
changing;
f) Environmental changes in our
industry are unpredictable.
Network actors’
emergence
Teece
(2007);
Wang and
Ahmed
(2007);
Pavlou and
El
Sawy
(2011);
Zollo and
Winter
(2002)
Schilke
(2013)
a) Business partners
provided important
information and insights
which helped to sustain
and improve
organizational
performance;
b) External networks were
sustained and enlarged;
c) Company demonstrated
trust in its partners;
d) How much of your time
did you devote to the
establishment of new
networking;
e) Where the establishment
of new networking efforts
fruitful?
f) The company often take
the initiative in
approaching firms with
R&D alliance proposals;
(INV-01, 6.2)
(INV-01, 6.3)
(INV-01, 11.2.8)
Networking (GEDI)
Fear of failure
(GEM)
17
g) Compared to our
competitors, we are far
more proactive and
responsive.
Identification of
client needs
Teece
(2007);
Wang and
Ahmed
(2007);
Pavlou and
El Sawy
(2011); Zollo
and Winter
(2002)
a) During the crisis the
company clients provided
valuable information and
insights for future
development;
b) The company had a lot of
alternatives to select
among clients and orders;
c) The company periodically
reviews the likely effect of
changes in business
environment on
customers;
d) The company often
reviews product
development efforts to
ensure they are in line
with what the customers
want;
e) The company frequently
determining market
characteristics and trends.
(INV-01, 5.1.5)
Taping
suppliers’ and
complementors’
actions
Teece
(2007)
a) The company suppliers
provided significant
information and insights
for future development
and competitiveness;
b) The company consultants
provided valuable
information and insights
(INV-01, 10.1)
18
for future development;
c) Professional associations
(the company belongs to)
provided with valuable
information and insights
for future development;
Scanning of
competitors’
actions
Teece
(2007);
Wang and
Ahmed
(2007)
a) The observation of
competitor actions
provided valuable
information and insights
for future development;
b) Company regularly
appraising competitors
and their products – both
existing and potential;
c) The company have gained
strategic advantages over
our competitor.
Seizing
opportunities
–
the
managerial
ability to
establish
strategic
decision
making rules
and resource
allocation
processes.
Indeed, once
a new
Recognition of
non-economic
factors
Teece
(2007);
O’Reilly and
Tushman
(2008)
a) One of the main company
priorities was learning and
development of employee
competences, mutual
trust, openness and
employee involvement
into the management of
the company and changes
which were implemented
by the company
b) Key success factor of the
company was the
employee, team work, and
employees’ loyalty and
care about people
(INV-01, 5.2.4)
(INV-01, 5.1.4)
Selecting in Eisenhardt a) The implementation of (INV-01, 11.2, 1-7)
19
technological
or market
opportunity is
sensed,
managers
have to make
strategic
choices and
evaluate
investment
requirements.
Coordination
processes are
essential for
preparing
external
resources for
internal use
(Ambrosini &
Bowman,
2009).
technology,
products
and markets
and Martin
(2000); Zott
(2003);
Teece
(2007)
new technologies was the
key element of business
development;
b) One of the main company
priorities was search for
new opportunities,
experimenting and testing
of innovative solutions,
involvement of new
resources;
c) Key success factor of the
company was unique,
innovative products
and/or services;
d) One of the main company
priorities was entering
new markets, dominating
in the market, and setting
high targets, high
achievements and success
Corporate entrepreneurship
Dimensions Factors/Varia
bles
Indicators Authors
Primary Secondary
Pioneer
corporate
entrepreneur
Leadership
Multifactor
Leadership
Questionnaire
items:
My leader
exhibits
behaviour that
promotes high
World Economic Forum-
Executive Opinion Survey:
Senior management
positions are hold by
(1=Usually relatives or
friends without regard
to merit; 7= Mostly
professional managers
Guth and Ginsberg
(1990); Waldman et
al. (2004); Visser et
al. (2004); Todorovic
and Schlosser (2007);
Ling et al. (2008);
Yukl (2010);
McCarthy et al.
20
levels of trust
amongst
his/her
associates and
followers,
which translate
into them
displaying a
strong sense of
purpose and
perseverance to
achieve the
most difficult
objectives;
My leader
articulates an
attractive
future that gets
the attention
and stimulates
the imagination
of his/her
associates and
followers;
My leader
stimulates
associates and
followers to
approach many
typical
problems by
questioning
assumptions
that have been
chosen for merit and
qualifications).
European Survey on
Working Conditions:
Your immediate
manager / supervisor:
provides you with
feedback on your work;
respects you as a
person; is good at
resolving conflicts; is
good at planning and
organising the work;
encourages you to
participate in important
decisions.
(2010)
21
used previously,
and by
encouraging
them to look at
the problem
from many
different
angles;
My leader
shows his/her
associates and
followers that
he/she
understands
their
capabilities,
needs, and
desires, and
works to
develop each of
them to their
full potential;
My leader’s
associates and
followers trust
him/her and exhibit
the values he/she
portray. The
associates and
followers are
committed to
achieve the
common vision,
even if sacrifices
22
are necessary;
My leader sets
goals to help
clarify, through
either
participative or
direct means,
what is
expected of
his/her
associates and
followers, and
what they can
expect to
receive for
accomplishing
these goals and
objectives;
My leader
systematically
looks for and
monitors
mistakes, and
takes corrective
actions when
mistakes occur;
My leader waits
for matters to
be brought to
his/her
attention about
something that
has gone wrong
before he/she
23
considers taking
corrective
action;
My leader
avoids taking
stands on
issues, clarifying
expectations
and addressing
conflicts when
they arise.
Corporate
strategy
Strategic
renewal
efforts
Zahra (1996)
Over the past
three years
company:
Has created
new semi and
autonomous
units;
Has changed its
competitive
approach for
each business
units;
Has redefined
the industries in
which it
competes;
Has recognized
operations,
units, and
divisions to
ensure
increased
CIS:
R&D expenditure as a
percentage of GDP
(R&D intensity);
Goals that were
important to the
enterprise (turnover
increase; increase of
market share; cost
reduction; increase in
profit margin);
Strategic goals that
were important to the
enterprise
(development of new
markets across EU or
associated countries;
development of new
markets across other
countries; expenditure
reduction within
enterprise; materials
cost reduction/cost of
Guth and Ginsberg
(1990); Zahra (1996);
Sharma and
Chrisman (1999);
McFadzean et al.
(2005); Ling et al.
(2008)
24
coordination
and
communication
among business
units;
Has introduced
innovative
human resource
programs;
Has been first in
the industry to
introduce new
business
concepts and
practices.
services reduction; new
or significantly
improved products or
services installation;
increasing the intensity
and improvement of
product marketing;
increasing enterprise
flexibility; development
of cooperation
agreements with other
enterprises or
institutions);
Factors that were
important as a barriers
for the enterprise
(strong price
competition; strong
competition in the
fields of product
quality, image or
product brand; low
demand; innovations
introduced by
competitors;
dominance of
competitors in the
market; shortage of
qualified personnel;
shortage of float;
difficulties or the high
cost of entering new
markets; the high cost
associated with country
Risk-taking Covin and Slevin:
Higher
propensity to
take risks;
Great deal of
tolerance;
Employees
encouraged to
take calculated
risks with new
ideas;
Supports small
and
experimental
projects;
The term ―risk
taker is
considered a
positive
Covin and Slevin
(1991); Antonic and
Hisrich (2001);
Nieman et al. (2003);
McFadzean et al.
(2005); Morris et al.
(2008); Bulut and
Yilmaz (2008); Singer
et al. (2009); Hill
(2009); Rauch et al.,
(2009); Parker and
Collins (2010);
Kuratko et al. (2011);
Shamsuddin et al.
(2012); Duobiene
(2013)
25
attribute for
people.
regulations).
GEM questionnaire (Adult
Population Survey APS)
Risks taken by
employees (loss of
status; damage to
career; loss of job; loss
of own money
invested)
Proactiveness Covin and Slevin:
Initiation of
actions;
Strong tendency
to be ahead of
competitors;
Company is
often first to
introduce new
products/servic
es using new
technologies;
Company often
shapes the
business
environment by
introducing new
products, new
technologies or
new
administrative
techniques.
Organizationa
l structure
Organisational
structure
enables/allows
easy
collaboration
across business
units/functions;
The
organisational
structure
World Economic Forum-
Executive Opinion Survey:
Characteristics of
corporate governance
by investors and boards
of directors (1=
Management has little
accountability to
investors and boards;
7= Investors and boards
Hitt and Ireland
(2011), Kuratko et al.
(2011)
26
establishes
clear roles and
responsibilities
of employees;
The
organisational
structure is
flexible and
changes as
needed;
The
organisational
structure has
many levels of
authority.
exert strong
supervision of
management decisions)
Performance
management
Rewards; Hornsby:
The rewards I
receive are
dependent
upon my work
on the job;
My supervisor
will give me
special
recognition if
my work
performance is
especially good;
My supervisor
will increase my
job
responsibilities
if I am
performing well
Eurostat: Structure of
Earnings Survey:
Annual Bonuses and
allowances not paid at
each pay period;
Eurostat:
Annual bonuses as % of
annual earnings
(enterprises with 10
employees or more)
World Economic Forum-
Executive Opinion
Survey:
The extent to which
management
compensation in your
country is based on
performance rather
than fixed salaries
Covin and Slevin
(1991); Antonic and
Hisrich (2001); Baum
et al. (2001); Hornsby
et al. (2003); Kuratko
et al. (2005); de Jong
and den Hartog
(2005); Ling et al.
(2008); Hill (2009);
Villiers- Scheepers
(2012); Duobiene
(2013)
27
in my job.
Autonomy; Hornsby:
I feel that I
am my own
boss and do
not have to
double
check all of
my
decisions;
This
organizatio
n provides
freedom to
use my own
judgment;
I have the
freedom to
decide what
I do on my
job;
It is
basically my
own
responsibilit
y to decide
how my job
gets done;
I almost
always get
to decide
what I do
on my job;
The Global Competitiveness
Report 2012–2013:
Willingness to
delegate authority
(In your country,
how do you assess
the willingness to
delegate authority
to subordinates? (1
= low – top
management
controls all
important
decisions; 7 = high
– authority is
mostly delegated to
business unit heads
and other lower-
level managers)).
European Survey on
Working Conditions:
Ability to choose
your own order of
tasks; methods of
work; speed or rate
of work;
You have a say in
the choice of your
working partners;
You are able to
apply your own
ideas in your work;
28
I have much
autonomy
on my job
and am left
on my own
to do my
own work.
You can influence
decisions that are
important for your
work.
Time
availability
Hornsby:
During the
past three
months, my
workload
was too
heavy to
spend time
on
developing
new ideas;
I always
seem to
have plenty
of time to
get
everything
done;
I have just
the right
amount of
time and
workload to
do
everything
well;
My co-
European Survey on
Working Conditions:
Working time
arrangements set:
by the company /
organisation with
no possibility for
changes; You can
choose between
several fixed
working; schedules
determined by the
company/organizat
ion; You can adapt
your working hours
within certain
limits; Your working
hours are entirely
determined by
yourself;
You have enough
time to get the job
done;
You can take a
break when you
wish.
29
workers
and I always
find time
for long-
term
problem-
solving.
Management
support
Hornsby:
Money is often
available to get
new projects off
the ground;
There are
several options
within the
organization for
individuals to
get financial
support for
their innovative
projects and
ideas;
This
organization
supports many
small and
experimental
projects
realizing that
some will
undoubtedly
fail.
GEM questionnaire (Adult
Population Survey APS)
The extent to which
employer provide
support when
employees come up
with ideas for new
goods or services.
European Survey on
Working Conditions:
Your manager helps and
supports you.
Communicati
on
Communication
Satisfaction
Eurostat:
Internet access,
Antonic and Hisrich
(2001); Ulvenblad
30
Questionnaire
(CSQ)
developed by
Redding (1972):
Communication
about my
progress in my
job;
Personnel news;
Communication
about company
policies and
goals;
Communication
about the
requirements of
my job;
Communication
about
government
action affecting
my company;
Communication
about changes
in the
organization;
Reports on how
problems in my
job are being
handled;
Communication
about
performance
(accomplishme
broadband and mobile
connections to access
the Internet, use of
intranet and extranet,
website/homepage by
enterprises (% of
enterprises);
Enterprises' websites by
facilities provided and
by economic activity
(% of enterprises having
a website)
(2008)
31
nts, personnel,
financials and
failures) of the
company;
Extent to which
my superiors
know and
understand the
problems faced
by
subordinates;
Extent to which
company
communication
motivates and
stimulates an
enthusiasm for
meeting its
goals;
Extent to which
my superior
listens and pays
attention to
me;
Extent to which
the company’s
communication
makes me
identify with it
or feel a vital
part of it;
Extent to which
the company’s
publications are
32
interesting and
helpful;
Extent to which I
receive the
information
needed to do
my job
timeously;
Extent to which
conflicts are
handled
appropriately
through proper
communication
channels;
Extent to which
the grapevine is
active in our
organization;
Extent to which
my supervisor is
open to ideas;
Extent to which
horizontal
communication
with other
employees is
accurate and
free-flowing;
Extent to which
communication
practices are
adaptable to
emergencies.
33
Organizationa
l learning
There is
continuous
investment in
the skills of
employees;
New and
improved ways
to do work are
continually
adopted;
We view failure
as an
opportunity for
learning and
improvement;
Learning is an
important
objective in our
day-to-day
work.
Eurostat:
Enterprises providing
training, % of all
enterprises;
Cost of training as a %
of total labour costs of
all enterprises.
European Survey on
Working Conditions:
Over the past 12
months, have you
undergone any of the
following types of
training to improve
your skills or not?
(Training paid for or
provided by your
employer or by yourself
if self-employed;
Training paid for by
yourself; On-the-job
training (co-workers,
supervisors)).
Denison (1990); Hitt
and Ireland (2011)
Innovation
Aggregated
groups of
indicators
Variables Indicators Authors
Primary Secondary
Economic
and
innovation
performance
based
indicators
Innovation
input
indicators
R&D intensity
(absolute and
relative, as an
annual R&D
budget as a
percentage of
annual sales);
Community Innovation
Survey, Innobarometer,
European Innovation
Scoreborad, R&D and
technology intensity
(Parthasarthy and
Hammond, 2002),
(Kaplan, S. Winby, S.,
2007), (White, 2002),
Milbergs, Vorontas,
2006
34
Total R&D
personnel or
budget as a
percentage of
sales;
Investment in
gathering ideas
from outside;
Commitment to
differentiated
funding for
innovation;
Investment in
innovation process
and learning;
Share of
employees who
have received
training and tools
for innovation
(e.g., instruction in
estimating market
potential of an
idea);
Share of capital
invested in
innovation
activities:
submitting and
reviewing ideas for
new products and
services;
developing ideas
through an
35
innovation pipeline;
Percentage of
“outside” vs.
“inside” inputs to
the innovation
process (open
innovation);
Innovation
output
indicators
Knowledge based
indicators:
total number of
patents;
number of
patents filed in
the past year;
number of
publications;
Market based
indicators:
new products to
existing market;
number of new
products
(services,
businesses)
launched in new
markets in the
past year
Share of
revenue/profit
from products or
services
introduced in the
past X years;
Royalty and
Community Innovation
Survey, Innobarometer,
European Innovation
Scoreborad, R&D and
technology intensity
(Kaplan, S. Winby, S.,
2007); Milbergs,
Vorontas, 2006
36
licensing income
from patents and
other intellectual
property;
Risk/return
balance
indicators
Share of capital
invested in
innovation
activities:
submitting and
reviewing ideas for
new products and
services;
developing ideas
through an
innovation
pipeline;
Percentage of
“outside” vs.
“inside” inputs to
the innovation
process (open
innovation);
Number of new
products, services,
and businesses
launched in new
markets ;
Community Innovation
Survey, Innobarometer,
EIS
Kaplan, S. Winby, S.,
2007, Milbergs,
Vorontas, 2006
Innovation
process
based
indicators
Ideation and
conceptualiza
tion
Number of ideas
submitted by
employees;
Number of ideas
gathered from
outside; Number
of ideas screened;
Community Innovation
Survey, Innobarometer,
Gopalakrishnan and
Damanpour (1997),
(Chiesa, at all, 1996)
Martins,Terblanche
(2003), Kanter
(2000), Amabile
(1998), Ettlie, 1980,
37
Focus for
initiatives geared
toward building
repeatable and
sustainable
approaches to
invention and re-
invention;
Recognition and
its tools of need
for innovation;
Concept
generation and
decision about
undertaking
innovation and
ways to achieve it
(adoption vs
generation);
Extent of usage of
formal idea
generation and
support tools
constrained
optimization to
maximize output;
Economic and
benefit models
applied by firm at
ideation stage;
Formalized
optimization tools
using formalized
process of project
Harvey and Mills,
1970); (Kaplan, S.
Winby, S., 2007),
Bessant, 2006,
Schmidt, Feeland,
1992) (Hall, Nauda,
1990), (cooper at all,
1999, 2001), (Cebon,
Newton, 1999, etc.),
(Szakony, 1994), (Lee
at all, 1996)
38
selection;
Project selection
efficiency post-hoc
project results;
Feasibility
building and
development
Process
management
capabilities:
adoption of
innovation;
generation of
innovation;
development of
innovation;
Project
management
capabilities:
formal innovation
project
management
tolls, i.e. problem
finding solving
cycle project
efficiency (actual
budget, cost,
revenues);
Innovation
speed;
Innovation
schedule
duration;
Communication
and collaboration
in innovation
process:
Community Innovation
Survey, Innobarometer,
(Rogers, 1993; Wolfe,
1994); (Saren, 1984,
Wolfe, 1994),
(Bessant, 2003,
Chiesa at all, 1996),
(Hauser and
Zettlemeyer, 1997,
Elwood, Grimshaw,
Pandra 2013, (Chiesa
and Masella, 1994),
(Cebon and Newton,
1999); (Damanpour,
1991, Cebon and
Newton, 1999),
(Bessant, 2003, von
Hippel, 1986),
(Jassawalia and
Sashittal, 1999).
39
Internal and
external
communication;
Collaboration
with suppliers;
Collaboration
with customers;
Collaboration
with strategic
partners;
Team
performance;
Commercializ
ation (launch
and post
launch)
Market
feasibility
building and
monitoring;
Budget and
commitment to
market testing
and launch;
Share of new
product launches
per year;
Launch
proficiency;
Post launch
reviews;
Adherence to
launch and sales
schedule;
Community Innovation
Survey, Innobarometer,
(Verhaeghe and Kfir,
2002), (Balachandra
and Blockhoff, 1995),
(Yoon, Lilien, 1985),
(Atuahene – Gima,
1995), (Griffin and
Page, 1993)
Horizontal
innovation
management
processes
Knowledge
management,
Knowledge
sources for
innovation;
Knowledge
CIS, Innobarometer (Milbergs, Vorontas,
2006)
40
recognition;
Knowledge
adoption;
Knowledge
integration in
innovation
processes;
Knowledge
management
tools for
innovation at
different stages;
R&D knowledge
development for
innovation;
individual based
innovation
competence
development;
group based
innovation
competence
development;
Learning for
innovation
supporting
organizational
systems;
Absorption of
internal and
external
innovation
experiences;
Enabling learning
41
results for
innovation;
Development of
strategic
innovation
competencies
internally;
External sourcing
for innovation
ideas;
Support to
creativity for
innovation;
Internal
experience
based learning
for innovation;
Routine based
organizational
learning;
Customer
oriented
organizational
learning;
Networks Variety and
change of
networks at
initiation stage;
Variety and
change of
networks at
development
stage;
Variety and
CIS, Innobarometer All new stuff
42
change of
networks at
commercialisatio
n stage (DC and
CE indicators);
Innovation
network
orientation
(supply,
customer,
technology, R&D
or business
system);
Organization
al capabilities
for
innovation
Organizationa
l structure
related
determinants
Flexible and
initiative
supporting
organizational
procedures;
Distributed
decision making
rights;
Clear allocation
of innovation
tasks;
Competence and
project based
dynamic
organizational
structure;
Innobarometer
Organizationa
l
infrastructure
for innovation
Participation (of
users and
employees)
facilitating IT
platform;
43
Effective and
flexible
information and
innovation
experience
management
system;
Creativity and
cooperation
facilitating
physical
organizational
infrastructure;
Innovation
partnership
supporting IT
and physical
infrastructure;
Organizationa
l culture in
relation to
innovation
Organizational
climate
supporting
diversity of ideas
and opinions;
Value based
orientation
towards
innovation;
High tolerance of
innovation risks;
Organization
and
monitoring of
innovation
activities
Effective
management of
innovation
processes;
Effective system
44
of innovation
activity
monitoring and
results
measurement;
Effective and
precise
innovation
management
decision making;
Organizationa
l
communicati
on
Effective system
of innovation
activity
communication;
Knowledge
and learning
processes for
innovation
R&D knowledge
development for
innovation;
individual based
innovation
competence
development;
group based
innovation
competence
development;
Learning for
innovation
supporting
organizational
systems;
Absorption of
internal and
external
innovation
45
experiences;
Enabling learning
results for
innovation;
Development of
strategic
innovation
competencies
internally;
External sourcing
for innovation
ideas;
Support to
creativity for
innovation;
Internal
experience
based learning
for innovation;
Routine based
organizational
learning;
Customer
oriented
organizational
learning;
Strategy and
leadership
for
innovation
Innovation
strategy:
Explicit:
adequate
resource
acquisition;
allocation at the
strategic
planning level;
mission, goals
(Kaplan, S. Winby, S.
(2007), Palmer,
Kaplan (2007),
Bessant at all 2006,
(Petraite at al, 2012);
Tipping, Zefren,
1995), (Milbergs,
Vorontas, 2006),
46
and strategy
alignment
(innovation goals
match strategic
objectives, ,
general strategy:
System
dynamics;
Risk/return
indicators;
Explicitness of
Innovation
Strategy;
(Miller, Friesen,
1982),
Leadership: Share of
executives’ time
spent on
strategic
innovation
versus day-to-
day operations;
Share of
managers with
training in the
concepts and
tools of
innovation;
Share of
product/service
or strategic
innovation
projects with
assigned
executive
sponsors;
(Kaplan, S. Winby, S.
(2007), Bessant 2006
47
Competitiveness and competitive advantage
According to the proposed conceptual model based on Global Competitiveness index (2013-2014)
manifestation of entrepreneurship and innovation on the country level is one of the competitiveness
indicators in innovation economy. This is very important to note that the structure and relationship of the
variables and indicators might be different in industry or information based economy.
Table 3. Competitiveness and competitive advantage
Factor conditions
Determinant Indicator Unit of measurement
Authors
Hu
man
cap
ital
Population Age Structure
The working-age population Labor force, thousand The average life expectancy
Pct. Pers. Years
Mankiw, Romer and Weil, 1992; Barro, 1997; Barro, 2000; Krueger and Lindhal, 2003, U. Fratesi, 2004, J. Bagdanavičius, 2006, EC, 1999, A. Pocius, L. Okunevičiūtė-Neverauskienė, 2005, H. Armstrong, J. Taylor, 2004, M. Porter, 1990, J., D. Sepic, 2005, Poot, 2007.
Qualification of Population with higher education Pct. J. Poot, 2007, D. Sepic,
Number of
managers that
become leaders
of new category
businesses
Organizational
capabilities for
innovation
metrics;
Strategy and
leadership level
metrics.
48
population Lifelong learning rate ( Lifelong learning refers to persons aged 25 to 64 who stated that they received education or training in the four weeks preceding the survey (numerator)) The number of university students The number of college students
Pct. Pers. Pers.
2005, U. Fratesi, 2004, J. Bagdanavičius, 2006, EC, 1999, De la Fuente, 2003 Petrakis, Stamatakis 2002; Papageorgiou 2003, M. Porter, 1990, Lineta Ramoniene and Marius Lanskoronskis (2011), I-Shuo Chen · Jui-Kuei Chen 2011, Elena Nisipeanu, 2013
Migration of residents
Local Migration (Netto) International Migration (Netto) per 1 000 residents
Pers. Pers.
T. Lindh ir B. Malmberg 1999, J. Poot, 2007, Papademetriuo, Demetrios G. and Madeleine Sumption 2011.
Entrepreneurship rate
Operating enterprise units Number of individual economic entities
Units Units
Zahra, 1999; Sang M. Lee Suzanne J. Peterson, 2000, Kunasz, Marek 2009
Ph
ysic
al in
fras
tru
ctu
re a
nd
geo
grap
hic
al lo
cati
on
Car transport infrastructure inside the region
Total length of the state and local roads Part of state roads Part of the local roads with improved covering.
Km. Pct. Pct.
M. Porter, 1990, J. Blakely, 1989, Canadian Urban Institute, 1999, W. R. Vickerman, 2001, A. Jurkauskas ir kt., 2005, EC, 2004 a, 1999, T. Fleisher, 2003, , E. D. Sepic 2005 ir EC 1999, Phang 2003; OECD, 2005, Boopen 2006, Elena Nisipeanu, 2013, pradhan, Bagchi 2013 ,
Regional external accessibility by land
Length of the roads with E category
Pct.
M. Porter, 1990, D. Sepic (2005) ir EC (1999, Fleisher (2003), Phang 2003; ,Boopen 2006, Elena Nisipeanu, 2013, pradhan, Bagchi 2013
Regional external accessibility by air and water
Passengers of air transport Sea transport of goods.
Pers. Tones
M. Porter, 1990, D. Sepic (2005) ir EC (1999, Fleisher (2003), ), J. Houvari ir kt. (2001), D. Pinelli ir kt. (1998)
49
Phang 2003; pradhan, Bagchi 2013, Boopen 2006
IT infrastructure
Level of personal computers – households Level of Internet access – households
Pct. Pct.
S. Madon, 2000, Ch. Avegrou, 1998, R. Mansell, U. Wehn 1998, L. Press, 1997, L. Adam, 1996, D. Sepic (2005) ir EC (1999), M. Porter, 1990, Elena Nisipeanu, 2013
Healthcare infrastructure
The Health Institutions per 1,000 population.
Units Acemoglu et al., 2001; Rodrik et al., 2004; Glaeser et al., 2004; Caselli, 2005
Infrastructure of new construction real estate
Built apartments per 10 000 population Non-residential indoor area per 1000 population
Unit square meters
S. K. Rainisto ,2003, Elena Nisipeanu, 2013
Kn
ow
led
ge r
eso
urc
es
Infrastructure of studies
The number of university students The number of college students Number of researchers per thousand labor force
Pers. Pers. Pers.
M. S. Briochi, L Cassia (2005),J Houvari ir kt. (2001), M. Porter, 1990, Lineta Ramoniene and Marius Lanskoronskis (2011), I-Shuo Chen · Jui-Kuei Chen 2011.
Infrastructure of science
Patent applications to the State Patent Bureau Science jobs at the universities Technological science production at universities
Units. Monetary unit. Units
E. J. Malecki (2004), J. Ritsila, J. Haukka (2003), P. Ronde, C. Hussler (2003), M. van Geenhuizen ir kt. (2002) G. Mačys (2005), Steinberg, Arndt 2001; Mairesse, Mohnen 2004, M. Porter, 1990, Lineta Ramoniene and Marius Lanskoronskis (2011), I-Shuo Chen · Jui-Kuei Chen 2011.
Collaboration with other regional academic institutions
Contracts of bilateral cooperation of universities Universities participation in international academic programs
Units Units
M. S. Briochi, L Cassia (2005),J Houvari ir kt. (2001), Lineta Ramoniene and Marius Lanskoronskis (2011), I-Shuo Chen · Jui-Kuei Chen 2011.
Investments in R & D Research and development Pct. M. S. Briochi, L Cassia
50
expenditure, shown as a percentage of GDP (R&D intensity) Gross domestic expenditure on R&D (GERD) of business enterprise Gross domestic expenditure on R&D (GERD) of government sector
Pct. Pct.
(2005),J Houvari ir kt. (2001), Lineta Ramoniene and Marius Lanskoronskis (2011), I-Shuo Chen · Jui-Kuei Chen 2011.
C
apit
al
The country's investment attractiveness
Material investment per capita Index of material investment attracting
Monetary unit Coeff.
M. Blomstrom ir kt. (1992), Bosworth, S. M. Collins (2003), M. Blomstrom, A. Kokko (2003),
International dimension of regional investment attractiveness
Foreign Direct Investment per resident, Lt Index of Foreign Direct investment attracting Foreign Direct Investment intensity (% of GDP) Eurostat
Monetary unit Coeff. Pct.
M. Blomstrom ir kt. (1992), Bosworth, S. M. Collins (2003), M. Blomstrom, A. Kokko (2003), Jaćimović, Danijela (2012)
Demand conditions
Determinant Indicator Unit of measurement
Authors
De
man
d
exte
nt
and
st
ruct
ure
o
f lo
cal m
arke
t
Demand extent of local market
Population density of 1 square kilometer. Turnover of retail trade, motor vehicles and catering enterprises (excluding VAT) per 1 inh.
Pers. Monetary unit .
G. Mačys (2005), M. Porter, 1990, Juyoung Lee and Elena E. Karpova (2010)
Demand structure of local market
Urban population (percentage of total population)
Pct.
M. Porter, 1990, V. Ceccato, L. O. Persson, 2003, M. Wikhall, 2002, A. Freundt, 2002, Juyoung Lee and Elena E. Karpova (2010)
Loca
l m
arke
t co
nsu
me
r ex
acti
ngn
ess
on
p
rice
an
d
qu
alit
y
Rate of material well-being
Monthly average gross earnings per employee Average consumption expenditure per household member per month Persons receiving pensions (per 1000 working age population) People at risk of poverty or social
Monetary unit Monetary unit Pers. Pct.
M. Porter, 1990, V. Ceccato, L. O. Persson, 2003, M. Wikhall, 2002, A. Freundt, 2002, Juyoung Lee and Elena E. Karpova (2010)
51
exclusion (percentage of total population) Recorded criminal offenses (per 100,000 population)
Units
Ext
ent
of
ex
tern
alm
arke
t d
eman
d,s
tru
ktū
ra,
reik
lum
as
kain
ai
ir
koky
bei
, re
gio
no
ži
no
mu
mas
.
Export markets Proportions of local goods export in in the country's GDP. Income from exports per capita
Pct. Monetary unit
N. Kaldoras, 1970, R. J. Dixon, A. P. Thirlwall, 1975, G. Mačys, 2005, E. Meilienė, V. Snieška, 2005, H. Amstrong, J. Taylor, 2004,
Notoriety of region in international markets
Accommodation enterprises. Guests in accommodation establishments per 1000 population. Hotel occupancy rate
Units. Pers. Pct.
A. M. Rugmano ir kt. (1998), M. Porter, 1990. Juyoung Lee and Elena E. Karpova (2010)
Cluster development
determinants
Indicator Unit of
measur
ement
Authors
Related and
supporting industries
The geographical concentration
of economic activities
A new approach to the
combination of competition and
partnership
Close cooperation between
business, education and
government
Infrastructure, developed and
adapted to the cluster activity
Favorable policy of public
authorities in relation to cluster.
The
qualitat
ive
assessm
ent
R. Jucevicius et. al., 2007, 2005, Kauno
technologijos universiteto Verslo
strategijos institutas, 2003, P. Clancy ir
kt., 2001, W. Hill, J. F. Brennan, 2000,
L. Mytekla, F Farinelli, 2000, I. R
Gordon, P. McCann, 2000, Theo J. A.
Roelandtas, P. den Hertog, 1998, M.
Porter, 1990, 2000, C. Ketels, G.
Lindqvist and Ö. Sölvell 2012, Elena
Nisipeanu, 2013
Corporate
entrepreneurship
Leadership
Strategic renewal efforts
Risk-taking
Proactiveness
Organizational structure
Rewards;
Autonomy;
Time availability
The
qualitat
ive
assessm
ent
Guth and Ginsberg (1990); Waldman
et al. (2004); Visser et al. (2004);
Todorovic and Schlosser (2007); Ling
et al. (2008); Yukl (2010); McCarthy et
al. (2010), Covin and Slevin (1991);
Antonic and Hisrich (2001); Nieman et
al. (2003); McFadzean et al. (2005);
Morris et al. (2008); Bulut and Yilmaz
52
Management support
Communication
Organizational learning
(2008); Singer et al. (2009); Hill (2009);
Rauch et al., (2009); Parker and Collins
(2010); Kuratko et al. (2011);
Shamsuddin et al. (2012); Duobiene
(2013), Hitt and Ireland (2011),
Kuratko et al. (2011)
Innovation,
Inovation
management
Innovation input indicators
Innovation output indicators
Risk/return balance indicators
Ideation and conceptualization
Risk/return balance indicators
Ideation and conceptualization
Ideation and conceptualization
Commercialization (launch and
post launch)
Knowledge management,
Networks
Management techniques for
Innovation
Innovation strategy:
Leadership:
The
qualitat
ive
assessm
ent
(Kaplan, S. Winby, S. (2007), Palmer,
Kaplan (2007), Bessant at all 2006,
(Petraite at al, 2012); Tipping, Zefren,
1995), (Milbergs, Vorontas, 2006),
(Miller, Friesen, 1982), (Verhaeghe
and Kfir, 2002), (Balachandra and
Blockhoff, 1995), (Yoon, Lilien, 1985),
(Atuahene – Gima, 1995), (Griffin and
Page, 1993)
Sample, unit of analysis and data source
Sample
The sample is innovative technological SME with 50 - 300 employees. The size of the SME was selected to
reflect typical SME size in Lithuania. Most of the firms are rather small – up to the 99 employees. However
in order to observe corporate entrepreneurship, organisational learning as well as innovation development
processes larger SMEs were selected as well. Most of the organisational phenomenon may be observed
only when the number of employees exceeds 100. Also 3 criteria were applied selecting the sample: (1),
firms with governmentally supported R&D projects (2) firms that possess intellectual property (patents or
copyright application) and (3) firms that invested more than 3 percent of sales in R&D. To select technology
intensive firms, we sampled firms in Information and communication technology, biotechnology, and
53
electric or electronic sectors. On the basis of these criteria, 112 firms were selected into our sample.
Sample is limited due to the selection criteria to invest in R&D – only small part of the firms actually invests
in R&D in Lithuania. Most of the cases firms by the technology. The Unit of analysis is firm. Respondents in
primary data selection process are firm managers.
Data source
To meet the aim of the research primary and secondary data sources are used. Primary data are mainly
used in testing the model and secondary data are used partially to validate primary data and also for the
development of the Dynamic capability index.
For the primary data several data sources were employed matching the research design (table 3)
Table 4. Data sources across selected research design
Research design Data source Nature of the data
Case study Interviews, observations, balance-
sheet, web page
Qualitative and quantitative data
Survey Structured questionnaire Quantitative data
Experiment Report of the experiment,
observation, interviews
Qualitative and quantitative data
Index construction Secondary data from Eurostat,
GEM, GEDI, GCI (Davos), Inno-
barometer
Quantitative
Variables
Independent variables are dynamic capabilities view based competitive advantage and dependent variable
ir country competiveness. The indicators of the variables are described in table 2 and 3.
Data analysis methods
Data are analysed using qualitative data analysis method as well as with the help of SPSS 16. To test the
model CFA is applied. Also correlation and regression analyses are conducted in order to set the
relationships between the major parameters. Also descriptive statistics is used including chi square.
54
Discussion, limitations and conclusions
The major need of the current literature is to develop clear structure and eliminate overlap between
Dynamic capabilities view, competitive advantage, corporate entrepreneurship, innovation, organisational
learning concepts. Also the research aims to establish relationships between Dynamic capabilities view
based firm competitive advantage and country competitiveness in transition to innovation economy.
The aim is very complex and multilateral, however investigating phenomenon bottom up (studying each
concept and discipline separately) and top down (constructing logical framework of interrelations between
the concepts and disciplines) in several cycles the holistic picture becomes clear.
The major challenge is to eliminate the overlap of the indicators coming from the different disciplines. The
issue is that different disciplines have different terminology for defining the same phenomenon. That’s
why picture 2 puts indications which variable comes from what discipline or from several.
The limitation of the research is that at this stage we do not include change management variable and
accordingly indicators, partially as it is covered by corporate entrepreneurship, partially due to the scope of
the study. Also Change management is least overlapping concept. Also the limitation is that the model is
developed to match innovation economy needs. Currently only first quarter of the EU member states are
within this stage. However this makes the research especially interesting as the research results should give
some clarity how to used dynamic capabilities view to build firm competitive advantage and in that way to
contribute to the country competiveness. It is very important to note that country competiveness entail
country level innovations and entrepreneurship as a distinctive feature of innovation economy.
The next step is to put research model and to develop research tools in order to empirically validate the
model and to test the relationships.
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