Regional innovation systems have been primarily developed in close interaction with policymaking and used widely as a framework for the design, implementation, and evaluation of innovation-based regional policies in most developed and developing countries and regions [1
]. The approach is based on the notion that regional competitive advantage is increasingly innovation-based and that innovations emerge when existing knowledge is continuously reconfigured into new combinations in local contexts [2
]. At the outset, it is important to consider why the concept of territorial innovation systems is being considered in this paper as opposed to regional innovation systems. In essence, it is because the concept of the “region” remains vague and elusive. The debate has been ongoing for almost two decades. For example, Doloreux and Parto [3
], although there was still a lack of consensus in terms of defining a region, suggested that the term “region” had become an economic policy focus in Europe and elsewhere [3
]. However, prior to Doloreux and Parto, Cooke [4
] and Cooke and Schienstock [5
] proffered two suggestions as to how to define region [4
]. The first was as a geographically-defined, administratively-supported arrangement of innovative networks and institutions that interact heavily with innovative outputs of regional firms on a regular basis, and the second was as a “georegional” territory based on the cultural aspects of the region. In 2011, the Organisation for Economic Co-operation and Development (OECD) defined region in general terms as referring to the administrative or political units that are at the first tier below the national level [6
]. However, they also stated that a functional region based on economic linkages might not match political borders and can span regional or even national boundaries. Therefore, examining a broader context than region, in other words, “territory”, brought the authors’ attention to an interesting and stimulating paper presented by Peyrony titled, Territorial cohesion: What scales for policy intervention
]. In the presentation, Peyrony intimated that there is a need to delimitate functional areas to help to target actions; to compare territorial units with similar functions across the whole of the EU [7
]. He continued that no comparable data is available and that such evidenced-based research is required to provide this comparative data. It was the identification of this need that spurred the authors of this paper to explore and develop a strategic competence model for understanding smart territorial development.
Territorial innovation systems have been the subject of intensive attention by academics and policymakers since the concept of national innovation systems was proposed by Lundvall [8
] and Freeman [9
], with a substantial body of literature being added continuously to the present day. While the concept initially focused on the flow of technology and information among organisations, institutions and even individuals to explain innovative and developmental performances at the national [11
], leading some researchers to claim that there was a national bias in the identification of actors, inter-relationships and attributes operating on a sub-national scale [14
], it became accepted relatively early that innovation has a strong locational or geographical component [15
] in which context-specific and intangible social, institutional and cognitive aspects play an increasingly important role [18
]. In particular, cognitive structures bring a certain degree of isomorphism to regionalisation, which becomes visible in, for example, the use of archetypes, i.e., trying to copy successful regions without reflecting on conditional differences [19
]. The predominant focus today is on regional and even local innovation systems.
However, although we are now all living in a regional world [20
] in which regions must compete with every other region on a global market [21
], it has been recognised long ago that a region’s ability to respond to global challenges varies immensely [22
]. Regions, from a conceptual perspective, not only constitute the basis for the process of addressing global challenges, but they are also a product of the process in that they keep undergoing change [19
]. Although we have a joint EU strategic approach framed by the grand strategy, Europe 2020, with its emphasis on smart, sustainable and inclusive growth [23
], which is also a core dimension in the Agenda 2030 framework, as well as the new grand strategy also accepted by the United Nations, and the Smart Specialisation Strategy approach [16
] to work from, we also have access to a plethora of good practices, exchange programmes, regional, national and macro-regional initiatives to inform our research. Therefore, our summary is that it is an empirically observable fact that some regions succeed and others fail; in some cases, they fail dramatically. The authors of this paper contend that the differences between how regions differ in their approaches to addressing global challenges lie, at least partially, in the strategic competences of regions, which determine their ability to adjust to new challenges [18
2. Materials and Methods
In this paper, we conceptualise and propose a two-layer model for describing and categorising the strategic competence of territorial systems of innovation at various levels. In this research, strategic competence includes the theory on the articulation of interests and coordination and strategic connection for engagement between actors and levels. This enables us to start tackling one of the major gaps in research on regional systems of innovation, namely the missing true evolutionary dimension of regional innovation systems and the factors that can impact regional transformations, as identified by Doloreux and Porto Gomez [25
] in their systematic literature review of an extensive body of literature on the topic extending almost two decades. They concluded from the body of research they analysed that the research would benefit from adopting a more dynamic approach “that would consider regional innovation systems as real, complex evolutionary systems wherein new actors can emerge and/or the roles of ‘traditional’ actors can mutate, thereby affecting the production, commercialisation and business models that can be considered appropriate for a given region” [25
]. It is this concept of the evolutionary system whereby there is a jagged continuum of new actors emerging while the roles of traditional actors mutate that urged us to consider the conceptualising of a two-layer model in an attempt to debunk, or at least create a new understanding, to cope with the complexity of dynamic evolutionary systems.
We continue the paper by outlining our approach, based on Max Weber’s ideal types [26
], developed at the turn of the 20th century, which, if codified, can be used for the purpose of further empirical exploration. We then continue with determining the variable territorial focus, allowing us to extend our thinking beyond the administratively defined territorial units, most commonly referred to as regions, and instead focus on the territorial unit as defined by the realistically existing connections between strategic actors. Following this, we determine the key components of strategic competences: substantive knowledge
and strategic connections
. On this basis, we develop two layers of strategic competences, one for “actor level” and the other for “territorial unit”. Therefore, the combined strategic competence model for smart regional development is a multi-layer model. The first layer focuses on the actor (individual, institutional, organisational) level and uses ideal types to categorise each as “Conductor”, “Broker”, “Lone Wolf”, or “Rent Seeker”. The second layer, based on the analyse of institutions/organisations, enables us to categorise regions as “Pioneers”, “Absorbers”, “Drifters”, or “Laggers”. This research provides concepts for the characterisation of a territorial unit’s strategic competence while, at the same time, the competence model is flexible enough to allow for the diffusion of different regional nuances.
The next step in the research enquiry will be to use the two-layer model to perform an in-depth analysis of a large number of diverse territories in order to transform the concepts into measurable indicators for monitoring the progress of regional and territorial strategic competences. The model will be tested several times before it is published as an evidenced-based empirical tool for the analysis of regional and territorial strategic competences. It must be noted, therefore, that this paper is the development of a conceptual framework which we will use to construct the methodological and analytical structures to perform our empirical analysis.
3. Ideal Types and Territorial System of Innovation
Our thinking in developing the two-layer competence model for understanding smart territorial development was to follow Max Weber’s approach to the application of ideal types in social science research [26
], that is, to develop ideal types by selecting and accentuating key elements which are deemed crucial in developing strategic competence. This facilitated us the opportunity to delve into “a topic that is little known or explored” and to help us grapple with an “empirical reality… that is primarily [achieved] through a comparison of reality with the ideal type” [27
]. Considering that “ideal types are defined by specifying multivariate profiles that represent the ideal types of organisations identified in the theory” [28
], they can be used in empirical exploration to determine the extent to which each specific case conforms to or diverges from a specific ideal type. This does not negate the fact that “there must be a closer fit, than Weber standardly admits or allows between ideal-types and the usual or average manifestations and tendencies as empirically observable” [29
]. Developing ideal types “involves selectivity at the theoretical level, just as the interpretation of experience by agents involves selectivity at the existential level” [29
The creation of ideal types is not an exercise in taxonomy or classification. In fact, there is a substantial difference between the two. Firstly, while classifications and taxonomies help us to build the concept and to classify empirical instances of specific phenomena (based on the empirical from reality to concept), ideal types start as a concept. Secondly, ideal types have significant theory-building potential, as they are, if properly developed, relatively complex theoretical statements that should be subject to rigorous empirical testing [28
]. However, this does not necessarily imply generalisability. Even in small-n variety-oriented research (as in most case studies, including comparative case studies), there is a need to collect a multitude of data [29
The decision to create ideal types has important implications for research on strategic competences. Firstly, one needs to be aware that ideal types do not represent real existing strategic actors, entities or territories. In fact, it can be assumed that empirical examples of ideal types are rare or if defined strictly, non-existent. Furthermore, empirically observable instances “may be more or less similar to an ideal type, but they should not be assigned to one of the ideal types in the typology” [28
]. Secondly, ideal types are developed for describing complex phenomena. As a result, they are described in terms of multiple dimensions, and each ideal type represents a unique combination of dimensions. According to Doloreux and Parto [25
], examples of studies following this approach are case studies that provide analysis of individual regional innovation systems, assessing the extent to which they correspond to a “truly regional innovation system” [25
5. A Proposed Model for Categorising Strategic Competences
To delineate the basis for the construct and structure of the strategic competence model for understanding smart territorial development, the following details, descriptions and analogies are presented. Here, it is important to note that the following is presented primarily from the organisational perspective, but it also relates to the territorial perspective in order to develop the two key elements of strategic competence. To start, therefore, strategic competence consists of the ability to, firstly, articulate interests and, secondly, to engage in multi-actor and multi-level coordination activities. To develop the structure of the model, we selected and accentuated two key elements of strategic competence: (i) the substantive knowledge to explain the articulation of interests and coordination among innovation actors and (ii) the strategic connection, to explain coordination.
is the precondition of the articulation of interests. This has two components: self-referentiality (knowledge about one’s operations, capabilities and limitations) and reflexivity (knowledge about one’s position in the environment and one’s influence on the environment). Self-referentiality is used to establish to what extent an organisation possesses self-awareness about itself, its organisation structure, and its operations. It establishes to what extent the organisation’s management and staff are aware of their core business and the resources (human, financial, technological and structural) required to manage their organisation successfully. This component seeks clear evidence of this self-awareness using internal documentation, such as the organisation’s business and/or operations plans, and external documentation, such as industry reports, published papers available in the public domain, and government documents. Reflexivity pertains to the extent to which an organisation is fully aware of its role and contribution to other organisations in the location within which it is based. Internal and publicly available documents can be used to establish an organisation’s role and contribution to its ecosystem and operating environment using techniques such as STEEPLE (Social/Demographic, Technological, Economic, Environmental, Political, Legal, and Ethical) at local, regional, national and global levels [56
These two components, self-referentiality and reflexivity, depend greatly on the organisation’s (or other emergent strategic organisation’s) structure, governance, culture, and management style. According to Mintzberg’s [57
] seminal work, organisations, in general, fall into one of five separate structures that fit different organisational types; they are (i) entrepreneurial, (ii) machine, (iii) professional, (iv) divisional, and (v) innovative. Each structure demands and brings about a different set of governance styles, processes and procedures. For example, a professional structure demands a bureaucratic configuration that relies on the standardisation of skills rather than work processes or outputs for its coordination and so emerges as dramatically different from the machine bureaucracy, which is very hierarchical with many layers from top to bottom of the organisation. In contrast, a divisional form of structure comprises many sub-entities (for example, multinational enterprises (MNEs) with subsidiaries in many different jurisdictions, which by their nature are sometimes centrally controlled by the parent company’s processes, procedures and norms. At other times, the sub-entities/subsidiaries are loosely controlled. Nevertheless, in either case, the ultimate governance or decision-maker is the parent company.
Therefore, as regards an organisation’s substantive knowledge, a critical point to note here is that the culture, not only of the organisation but also of the territorial unit in which it resides and operates, as well as the management style of the owner/manager and/or the organisation’s senior executive; and whether the organisation is a public, private or third sector entity, have an impact on an organisation’s depth of substantive knowledge. For example, a highly structured, hierarchical, multi-layered organisation based in a closed-market and restrictive society is less likely to have a permeable depth of self-referentiality and reflexivity compared to an entrepreneurial style organisation with few governance layers in an open-market, open-society environment.
is the ability to engage in communications and networking to define common interests, thereby achieving certain levels of coordination and synergy [58
] and, if possible, enabling “more imaginative, inclusive, and legitimate strategic spatial planning” [59
]. Strategic connection has three components: (i) connections, (ii) contributor/absorber and (iii) influencer (as in the perceived influence of the identity). The connections component is used to determine the extent to which an organisation is connected to other organisations in its own region and in other regions as well as organisations within its own sector and with other sectors. The component contributor/absorber is used to establish the extent to which an organisation is a “contributor” to its sectoral and locational environments or, indeed, to establish the extent to which the organisation “absorbs” resources from its surrounding environment. The component term influencer is used to understand the organisation’s perceived degree of influence within the region and sector in which it is based. This is very much a subjective assessment. In other words, to what extent does the organisation influence strategic content and direction for the location in which it is based and the industry sector within which it operates?
Another critical point to note here is that the degree to which strategic competence exists in an organisation or territorial unit also depends on the organisation’s structure, culture and management style as well as the governance and societal structure of the territorial unit in which it is based and operates. From an organisational perspective, if the organisation’s management style and culture are open to learning and the sharing and exchange of knowledge, experience, expertise, technology (process and product) and innovation, then it will be susceptible to engaging, networking and communicating with other entities within (and external to) the territorial unit within which it is based and operates. Such organisations are more likely to have high degrees of strategic competence compared to organisations that are overly protective of their intellectual property (IP), processes and procedures, that lacking in trust when dealing with primary and secondary stakeholders, and/or lack the capacity and capability to absorb experiential learning [60
] from other entities. Equally, entities that are more active in Corporate Social Responsibility (CSR) and employ management and governance practices that address societal and environmental needs are more likely to possess strategic competence than those that do not engage in these activities.
An organisation’s strategic competence also depends on the degree to which it is embedded and the significance of its role within the territorial unit in which it operates. For example, the extent to which the organisation is the dominant large-scale employer, idealist dominator (religious, political, or both), or significant benefactor in the community will significantly impact the degree and depth of the influence component of its strategic competence. From a territorial unit perspective, regions and municipalities that are structured and governed to engage with cross-border and inter-regional activities in an open-market, open-innovation, open-society environment [61
] are more likely to possess strong strategic competence compared to their counterparts that are not structured or governed to engage in cross-border or inter-regional activities.
In summary, the conceptualisation and articulation of the two key constructs of strategic competence: (i) substantive knowledge and (ii) strategic connection, which leads us to the two-dimensional model of strategic competence as shown in Figure 1
The degree to which a strategic entity (organisation or territory) has developed both substantive knowledge and strategic connection will determine the strategic competence of that entity. The entity could be a singular Higher Education Institution (HEI), an enterprise (be it indigenous or multinational), a government agency, a civic society organisation (CSO) or even an influential individual) (micro-level) with limited influential capacities and capabilities, or it could be a dynamic collection (or network) of influential actors with emergent properties. Emergent properties are jointly shaped by the presence and actions of micro-level (singular) actors. However, due to their emergent nature, they are also shaping the actions of these micro-actors.
As a result of strategic competences being determined by two dimensions, the strategic competences are not a continuum; instead, they are in a two-dimensional space that enables the determination of four distinct ideal types of strategic competences. Furthermore, we are presenting two sets of ideal types because we are proposing a two-level model. The first set is at the actor level (individuals, organisations, networks, etc.) of strategic competence (see Figure 2
). This can be used to describe and analyse the strategic competences of individual and collective actors at a micro level. The second set can be used to describe and analyse the strategic competences of territorial units (see Figure 3
Within each set, there are four quadrants suggesting four ideal types of strategic competences. In our deliberations and critical analysis, we did consider merging the actor and territorial levels into one overlapping dimension. However, we found that this added hugely to the complexity of delineating and articulating the essence and critical aspects of the strategic competence model. Therefore, it was decided to keep the analysis and explanation at both (i) the actor and (ii) the territorial level while at the same time being conscious of and fully appreciating the dynamic interplay, influence and determination between both levels.
5.1. Actor Level of Strategic Competence
The four types of strategic competences of individual and collective actors are the conductor, lone-wolf, rent-seeker and broker.
The Conductor in Quadrant I of the actor level strategic competence model is the type of actor that has a very high degree of both strategic connection and substantive knowledge. As regards strategic connection, the conductor will have many strategic and operational connections with organisations in their own as well as other sectors and within their own and other regions. The Conductor will have both high degrees of absorptive capacity and be adept at absorbing relevant resources from other organisations to support the development and sustainability of their own organisation. At the same time, these organisations have the capacity and capability to, and actively do, support the development of other organisations. Such organisations are open to networking and knowledge sharing, and experiential exchange. Finally, the Conductor is an important influencer on a large scale in that these organisations visibly provide relevant support to other organisations, thereby influencing the positive development of the sector and location within which they are based.
As regards substantive knowledge, the Conductor demonstrates strong dimensions of self-referentiality (knowledge about its own operations, capabilities and limitations) and reflexivity (knowledge about its position in advancing, enhancing and influencing its region’s socioeconomic environment). The Conductor is equally capable of engaging and collaborating with other organisations, thereby contributing to its region’s goals. In summary, the Conductor is an influential collaborator and coordinator that engages strategically with other organisations in its region.
The Lone Wolf in Quadrant II is also very high on substantive knowledge but low on strategic connections. In such instances, the organisation has high degrees of knowledge about its own operations, capabilities and limitations. The organisation may equally possess a strategic intent that contributes to enhancing the socio-economic development of its region, but it does not effectively engage or collaborate with other organisations in the region. On the other hand, these organisations are very protective of their processes and procedures and rarely share these with other organisations. Therefore, the Lone Wolf has few Strategic Connections.
The Rent Seeker in Quadrant III is an organisation that uses regional and societal resources to obtain economic gain without reciprocating any benefits to society through wealth creation. Rent Seekers are generally self-focused entities that are not aware of or do not actively develop their competences or capabilities and do not actively contribute to the enhancement of the socioeconomic development of their regions. Senior and middle managers of such organisations frequently display mistrust of management in other organisations and are generally not proactive in addressing societal or environmental change. Invariably, Rent Seekers are independent organisations with few strategic connections within the region in which they operate.
The Broker in Quadrant IV is an organisation that is good at coordinating other organisations; therefore, they possess high degrees of strategic communication. These organisations are collaborators, match-makers, business network organisers, and/or possess (often own) the resources (for example, public bodies and/or government agencies) to enable other organisations to network. A Broker’s role is functional/operational and, therefore, generally does not possess high degrees of substantive knowledge.
5.2. Territorial Unit Level of Strategic Competences
From a higher order or collective perspective level, the ideal categories of strategic competence of territorial units are depicted in Figure 3
. The four ideal types are Pioneer, Drifter, Lagger and Absorber
The macro-level is concerned with a collaborative and cooperative collective of entities located within a given territorial unit. This is a complex scenario as the collaboration and cooperation include engagement with entities on the same level (for example, other regions) as well as at multi-level (national, macro-regional).
The Pioneer in Quadrant I is a territorial unit with high degrees of strategic connections and substantive knowledge. Pioneers have strong strategic connections in that they have a critical mass in quantity and level of connections with intra-regional entities as well with international organisations. Pioneers also have strong substantive knowledge, which is demonstrated by their high levels of human capital, innovation capacity and capability, advanced technologies, digitalisation, and the constructive application of their entrepreneurial discovery processes. Therefore, the essence of Pioneer regions is that they have a broad breadth of stakeholder engagement focused on the enhancement of inclusive and sustainable regional socioeconomic development to the benefit of all its citizens. In general, the Pioneer territorial unit engages stakeholders in an inclusive collaborative dynamism whereby the processes of responsible research and innovation (RRI) are embedded in the region, and policies are in place to address grand societal challenges and environmental needs.
The Drifter in Quadrant II is a region that has high degrees of substantive knowledge to the same extent as Pioneers but possesses low levels of strategic connections. As a result, these regions “drift” because they are not sufficiently connected to strategic alliances within their respective regions or internationally. The strategic intent of the region may not be aligned with leading organisations in the region.
The Lagger in Quadrant III is a region that is low in both strategic connections and substantive knowledge because such regions do not have good strategic connections within their region or internationally and because their social capital and innovation levels are low. Also, because their industry base has not been modernised, these regions become less attractive to inward investment and therefore become Laggers.
The Absorber in Quadrant IV is a region that is high in strategic connections but low in substantive knowledge. Such regions are good at making national and international connections and attracting inward investments. However, they are not good at using their strategic connections or investing in infrastructure or human capital to advance the socio-economic development of their region.
The next step in the development and research application of this strategic competence model will be its operationalisation. This will be achieved through a set of both qualitative and quantitative criteria and analysis, which will enable us, in line with ideal types methodology, to determine the deviation of selected actors and territorial units from “ideal types”. In defining a set of qualitative and quantitative criteria, we will consider crucial research (particularly recent research) that has addressed qualitative and quantitative criteria in innovation systems and regional development [62
]. Therefore, it must be noted that the end goal is not to assign individual actors or territorial units to specific quadrants but rather to describe their deviation from an ideal type. For example, when analysing the territorial unit of Silicon Valley, the epitome of high technology and innovation, or Baden-Württemberg, the epitome of the prosperous German automotive industrial powerhouse, it will not result in assigning either the ideal type of a Pioneer. Instead, we will provide a description as to how the entity deviates from an idea type of either Pioneer, Drifter, Lagger or Absorber
. Also, when analysing the role of specific academic institutions or the role of funding organisations such as venture capital firms or banking institutions in the success of Silicone Valley or Baden-Württemberg, they will not be assigned an ideal type, but a qualitative description of their distance (deviation) from the ideal type.
6. Conclusions: Implications and Applications
In this conceptual paper, we have developed a model of strategic competences for understanding smart territorial development, following Max Weber’s ideal types approach. Our purpose was to provide a systematic theoretical composition and characteristics of ideal types delineating the strategic competence of actors within the context of smart regional development. Although our ideal types are not based on empirical analysis, in line with Max Weber’s approach, they are also not developed ad hoc. The ideal types are based on a simple yet integrated theoretical and conceptual schema, which have the potential to “produce extraordinarily rich explanations of social processes” [39
], in this case, complex, multi-actor and multi-layered processes of smart regional development. They also allow for the development of tools for the empirical analysis of strategic competences of both individual and collective (emergent) actors, which is necessary to develop robust explanations of smart territorial development. They also enable the mapping and explanation of many empirically observable nuances and the development of evidence-based policy proposals for smart regional development.
In developing reliable explanations of smart territorial development, we will draw on the findings of recent qualitative research and on research that uses (comparative) case studies in the fields of regional development and innovation systems as a research technique [65
Through the dimension of Strategic Connection, the model enables future analysis and possible policy proposals to consider the demonstrated “horizontal, variegated and combinative” [68
] nature of regional knowledge and innovation flows. This dimension also allows us to address another critical issue in the strategic development process, namely “the way in which people are excluded or included in planning process” [58
] in the empirical analysis of specific territorial nuances. When using the model in the future, in addition to some recent research that provides a relevant methodological framework for the design of empirical research from conception to implementation [69
], three key points need to be taken into account.
Firstly, the model does not focus on a single type of organisation, sector or region defined in strictly administrative terms (e.g., NUTS). Rather it can be applied to explore and categorise the entire set of entities operating at a specific territorial and geographic level. This includes not only the classical social partners (e.g., employers, trade unions, and the state) but also the infrastructure for the (re)production of knowledge (universities, institutes, and other knowledge providers), intermediary organisations (such as business incubators, and science and technology parks), NGOs and civic society organisations (CSOs). Where necessary and appropriate, this model can also address other relevant organisations, such as venture capitalists and business angels, international organisations whose activities impact the region. The model takes into account that these actors are vertically and horizontally disaggregated, but at the same time that they are also engaged in a continuous process of communication and coordination.
Secondly, inter-organisational linkages and institutional empathy do not imply that boundaries between individual organisations become blurred. Functional differentiation, as one of the key aspects of developed complex societies [65
], is clearly represented in the analytical model. However, strategic competences also include the capability for sophisticated forms of coordination required to neutralise inherent risks of functional differentiation. The need for the art of separation must be complemented by the art of communication.
Thirdly, strategic competence includes the ability to articulate interests and engage in the coordination of activities. Articulation of interests requires a certain level of technocratic competences. This has two components: self-referentiality (knowledge about one’s own operations, capabilities and limitations) and reflexivity (knowledge about one’s position in the environment and influence on the environment).
The major contribution of this conceptual paper is to both research and practice. As regards research, the model adds to the theory of innovation systems because it articulates concepts for describing the characteristics of strategic competence within the context of a territorial unit. Furthermore, this strategic competence model for smart territorial development, taking the multi-layer and multi-actor dimensions into consideration, is flexible and allows us to address regional nuances, facilitating the operationalisation of the model for future empirical research. The multi-level model forms the foundation for future research by transforming the concepts into a set of measurable indicators to determine the current strategic competence of regions and territories.
From a practitioner’s perspective, the model will be beneficial in preparing and articulating research-informed policymaking. In practical terms, the model can be used by individual or collective policy actors to determine the current strategic competence of a region or territory and to assist these influencers in policymaking to plan the strategic competence trajectory of the regions and/or territories within which they operate. On this basis, they will be able to co-design, co-develop, co-implement, co-measure, and co-evaluate Joint Action Plans (JAPs) for their respective regions and territories.