Cultural Tourism Routes as Incubators for Innovation and Economic Diversification: A Potential Analysis in the Framework of the New Silk Road Initiative in Azerbaijan

Arne Schuhbert 1 , Hannes Thees 2 , Valentin Herbold 3 , Johanna Weinreiter 4 , and Markus Kantsperger 5
  • 1 Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, Eichstätt, Germany
  • 2 Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, Eichstätt, Germany
  • 3 Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, Eichstätt, Germany
  • 4 Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, Eichstätt, Germany
  • 5 Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, Eichstätt, Germany
Arne Schuhbert
  • Corresponding author
  • Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, D-85072 Eichstätt, Tel. +49 176 354 325 36, Eichstätt, Germany
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, Hannes Thees
  • Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, D-85072 Eichstätt, Tel. +49 176 354 325 36, Eichstätt, Germany
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, Valentin Herbold
  • Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, D-85072 Eichstätt, Tel. +49 176 354 325 36, Eichstätt, Germany
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, Johanna Weinreiter
  • Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, D-85072 Eichstätt, Tel. +49 176 354 325 36, Eichstätt, Germany
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and Markus Kantsperger
  • Chair of Tourism/Center for Entrepreneurship, Catholic University Eichstaett-Ingolstadt, Pater-Philip-Jeningen Platz 2, D-85072 Eichstätt, Tel. +49 176 354 325 36, Eichstätt, Germany
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Abstract

Cultural routes are today a widespread phenomenon throughout the Industrialized Countries (IC) and have become more and more prominent as a tool for tourism development in recent years (Flognfeldt, 2005:37; Meyer, 2004:5). For countries in the Southern Caucasus, who profit from their bridging position between Europe and Asia, the planned revival of the Ancient Silk Road (ASR) in form of the New Silk Road (NSR) offers substantial potentials for economic diversification by means of tourism as a catalyzing industry. On the case of Azerbaijan, this study analyzes the potential to trigger regional economic diversification within the existing national destination-system in a framework of route development. To this end, the methodological approach builds upon a mix of qualitative and quantitative methods to diagnose the current degree of cluster maturity in the system, following the question of how Azerbaijan as a system of regional destination can access the transnational route system of the NSR.

1 Problem Description

Operating within a spatio-functional and historical continuum with the “Ancient Silk Road” (ASR) from the 1st century AD, the “Belt and Road Initiative” (BRI) or “New Silk Road” (NSR) was launched by the Chinese government in 2013 as a means to boost China’s westward economic integration. The NSR comprises the Silk Road Economic Belt (SREB) – the land route and the Maritime Silk Road (MSR). As a global development project, the NSR has cause and effect relations on different geographical scales and towards several economic sectors (Pechlaner et al. 2019). As a result, China has launched and supported numerous infrastructure projects in Asia, Europe and Africa and recently increased interest in Latin America. In the first instance, this might be seen as an infrastructure and trade system, but the NSR could be part of a global economic transition (Blanchard, Flint 2017, p. 223), which is based on increased connectivity, intermodal transportation, pipelines and hubs (Barisitz 2017a). So far, the Chinese initiative seems to be successful in terms of signed cooperation, which by July 2019 reached“195 intergovernmental cooperation agreements with 136 countries and 30 international organizations” (Belt and Road Portal 2019).

For countries participating in the initiative, it offers opportunities to tie into the proposed system of linked transnational infrastructural assets (such as railways, roads, bridges and tunnels) in order to concurrently develop their respective socioeconomic systems at a regional, national and international level (Pechlaner et al., 2019). This especially applies to Developing Countries (DC) in the Caucasus, which see their geographical bottleneck position within the NSR as an opportunity to boost and diversify their trade activities. Azerbaijan is aware of its geographical crossroads and its indispensable role for the BRI (Azernews 2019c). That’s why both countries signed a Memorandum of Understanding on the “joint promotion of the creation of the Silk Road Economic Belt” (SREB) in 2015 (Belt and Road News 2019; Azernews 2019c). Beyond infrastructure and the trade in goods, this also concerns trade in services such as tourism, as the immanent expansion of the European and Southeast Asian pleasure periphery (Steinecke, 2014) is most likely to result in rising demand for Caucasian destinations in the medium term.

Table 1:

Spatial scales and dimensions of the BRI, modified after Pechlaner et al., 2019, 4

Scale

Global

Transnational

National

Local or Regional

Case study

BRI

Development Corridors

Azerbaijan

Agglomerations and Hubs

Infrastructure

Gateways in trade and production

Corridors and transit systems to link local infrastructure within a global network, Trans-Caspian-Corridor

Example: BTK

State Development Program (set of initiatives and infrastructures)

Example: South-North Highway

Agglomeration of infrastructure and production around hubs

Example: Alat Port

Cluster

Transnational Linkage Network

National-Cluster-System

Regional-Sectoral Cluster

Tourism

Cultural Tourist Route, Cross Border Tourism

National Destination

Local or Regional Destination

However, since many regional and national destinations in the DC have to cope with infrastructural, political, economic and sociocultural obstacles (Schuhbert, 2013), the question arises: Under which circumstances are existing DC destinations within the reach of the NSR mature enough to make full use of the initiatives’ potentials for economic development? As research on this subject is just starting, the purpose of this study is to investigate this question based on the sample case of Azerbaijan in the South Caucasus. Following the fact that the NSR as a global development strategy affects different geographical scales, the case study of tourism in Azerbaijan needs to be classified. To this end, the analysis and discussion focus on the national level while at the same time including selected local perspectives (see Tab. 1). The goal of this analysis is then to draw conclusions regarding the connectivity between the tourism cluster system and cultural tourist routes on a transnational scale. Cultural tourist routes are thus understood as socio-psychologically constructed, spatial pipelines for goods and services but also for the exchange of individual ideas and knowledge (see 2.2.).

The tourism cluster approach has found increasing appreciation among tourism scholars and practitioners over the past decade as a means to propel the diversification of exportable goods and services and finally to promote regional economic development (Hall et al., 2003; Lejarraja & Walkenhorst, 2007; Thomi & Sternberg, 2008; Moric, 2013). Cluster approaches related and unrelated to tourism have found their way into the economic development policies of several NSR partner countries, which recently launched several initiatives to revive the ASR as a cultural tourist route (Schuhbert, 2018).

Despite this increasing importance of the concept, tourism cluster approaches have to our knowledge been very scarcely applied to the analysis of cultural routes and their functionalities for regional economic development in the DC. Based on a cluster-theoretical, analytical framework (section 2), the present study applies a mixed-method approach (section3) to the analysis of the sample case (section 4) in order to finally contribute to an improved scientific understanding of the mechanisms, potentials and requirements of national cluster systems and to provide policy makers with potential starting points for systematic, integrated planning between the NSR and the given tourism systems (section 5).

2 Creation of an Analytical Framework for Cluster Maturity

2.1 Cluster Systems and Lifecycle

Michael Porter (2008, 215), who has been very influential in the formation of the cluster concept, defines clusters as “a geographically proximate group of interconnected companies and associated institutions in a particular field, linked by commonalities and complementarities. The geographic scope of a cluster can range from a single city or state to a country or even a network of neighboring countries […] A cluster is a system of interconnected firms and institutions the whole of which is greater than the sum of its parts.”A growing number of publications (Capone et al., 2016; Schuhbert, 2013, 2018; also cmp. in the wider context of innovation systems: Ozseker, 2018; Trunfio & Campana, 2019) indicate that this conception also applies to the tourist destination, due to the location-binding and network character of the tourism product, therefore underlining the growing importance of tourism’s multiplier effects for rural regional development policies in the DC (Hall et al., 2003; Moric, 2013).

Building on growth pole theory, Porter (2008, 250) argues that the creation of a national system of clusters is a prerequisite for economic development and describes the respective problems of the DC as a result of an inappropriate cluster maturity. A rationale for this can be found in the problem of sustaining the emergence of those agglomeration and spillover effects that forge cross-sectoral network linkages among regional, national and international business actors in the course of the cluster lifecycle (cmp. Hall et al., 2003; Schuhbert, 2013; Moric, 2013; Ozseker, 2018). The related maturation process of cluster systems in the DC, initially modeled i.a. by growth-pole theorist J.P. Lasuen (1973) and later modified for tourism by K.Vorlaufer (1996), has found also partial representation and modification in recent debates on destinations as localised innovation systems (Ozseker, 2018; Trunfio & Campana, 2019) or ecosystems, which are to be conceived as adaptive, dynamic cluster systems on variable geographic levels (cmp. Isckia et al., 2018; Baggio et al., 2013; Gretzel et al., 2015). Delimiting the focus in the following on the “pre-colonial” stages of an emerging DC destination, with still limited external control through transnational companies (cmp. Letzner, 2010), the process can be traced in large parts along the stages of the cluster lifecycle approach by Andersson et al. (2004):

As Vorlaufer (1996, 196 et sqq.) describes for the emergence stage, early destinations in the DC are often geographically bound to the immediate vicinity of primate or gateway cities. An accumulation of tourist demand stimulates the genesis of geographically concentrated markets on the demand side, which can be specified analogously to Lasuen (1973, 164) as “geographical clusters.”

During the development stage, (cross-)sectoral linkages (“sectoral clusters”) may continuously attach complementary businesses to these markets on the supply side (cmp. Isckia et al., 2018; Ozseker, 2018). Despite the deficits in public support and infrastructures (see Letzner, 2010, 165), the creation and deepening of these tourism-induced linkages and synergies are used to substantially contribute empirically to economic diversification and development of the DC at this stage. This is primarily the case in tourism-specialized middle-income countries (Lejarraja & Walkenhorst, 2007; Sannassee et al., 2014; De Vita & Kyaw, 2017; Gwenhure & Odhiambo, 2017).

The evolutionary process finally reaches its theoretical optimum (mature stage) when a critical mass and variety of actors trigger self-sustaining dynamics in the creation of new, complementary business activities and their proactive (knowledge-creating/sharing) linkaging at the regional, national and international level (see 2.3.), powered by a co-location of regional and (often asymmetric) transversal sectoral networks in the primate destination (Ozseker, 2018; Trunfio & Campana, 2018). In the course of this consolidation stage, the dynamics between regional competitive and cooperative forces, the driving force behind new synergy and network potentials and thus for the maturation process as a whole, achieves a quality that results in the emergence of completely new types of complementarities in competences that facilitate a transition from an incremental to a transformative, radical change of the total cluster (cmp. Martinez-Ros et al, 2009; Hjalager, 2010; Trunfio & Campana, 2019). This includes cluster reproduction in another location – often powered by rising diseconomies of agglomeration in the primate city. At this stage, actors in a few primary clusters can make use of these newly emerged, transformative resources to finally spawn a geographically widespread, hierarchically gradated system of“regional-sectoral clusters” throughout a country (transformation stage; cmp. Lasuen, 1973, 170 et sqq.; Vorlaufer, 1996, 90 et sqq.; Meyer, 2004, 8 et sqq.; Walkenhorst, 2007; Letzner, 2010; Moric, 2013; Schuhbert, 2013, 89, 186; cmp. also Isckia et al., 2018).

As long as transportation costs remain high, as is still the case in many DC (for example due to missing technologies or infrastructures, etc.), the formation of new destinations remains tied to the settlement structure (Letzner, 2010, 145 et sqq.; Schuhbert, 2013, 187–188) and as the spatial hierarchic structure of settlements use to fluctuate strongly here, an emerging system of tourist clusters or destinations is likewise affected. As the instability of spatial structure and GNI use to correlate negatively as Lasuen (1969, 144) observes, these fluctuations in regional-sectoral cluster dynamics may impose variable local competitive pressure levels and finally an instability of agglomeration advantages and productivity (decline stage). This may constitute an autocatalytic downcycle on the deepening of cross-sectoral linkages, impeding the consolidation and maturation of a national destination-system and consequently of the process of economic diversification (cmp. Letzner, 2010, 169 and the “lock-in” of local clusters in Ozseker, 2018).

In light of these contributions, national tourism clusters may ideally be conceived as clusters of a higher order, hierarchically integrating a system of regional clusters with different levels of maturity (cmp. Moric, 2013). Here, a basic self-similarity or scalability of the structures is to be assumed, where the national cluster is based essentially on the same system logic as its local or regional components (Schuhbert, 2013, 89).

2.2 Cluster System and Cultural Tourist Routes

The concept of a national cluster or destination system is also applicable to a potential cultural tourist route (cmp. Moric, 2013) embedded in the NSR. As they may be defined as physical channels for “multi-dimensional, continuous, and reciprocal exchanges of goods, ideas, knowledge and values between peoples, countries, regions or continents over significant periods of time”(Zabbini, 2012, 62), these routes emerge as a result of highly segment-specific tourist flows, selectively connecting staging areas, stopover waypoints and gateways (destinations) through tracks in a spatial network pattern, which is also intertwined with a socio-psychological construction process of space (cmp. Hjalager, 2010). Analogous to a national tourism cluster (s. a.), spatial spread and concentration of tourist demand consolidate the hierarchical gradation of destinations in the route system (see Flognfeldt, 2005, 5, 38; Asero et al. 2015, 753), while the functionality of the system as a whole is dependent on the quality of linkages between the individual nodes or clusters of the spatial network.

Linkages, lining up individual regional-sectoral clusters like “pearls on a string,” expand the set of exchange relations existing among regional tourism service providers with a trans-regional or even transnational set of channels for the import and export of vital production factors (cmp. Ozseker, 2018). This concerns primarily the disposition of tourists (as “external production factors” in tourism; Bieger, 2008) and knowledge with a widespread consequence for the dynamisation of tourism cluster system development: As studies indicate that rising demand in regional clusters (s. a.) has positive effects on local and regional linkage creation and diversification (Lejarraja & Walkenhorst, 2007) and this, due to tourism companies` generally strong dependence on external knowledge sources, has a positive effect on the absorption of knowledge (and the other way around), the establishment of cultural routes connecting various regional destinations could substantially boost cluster-system maturation at a regional or national level (cmp. Hjalager, 2010; Schuhbert, 2018; Trunfio & Campana, 2019).

2.3 Maturity of Cluster Systems

The maturity of (tourism) clusters can be conceived as a function of their capability to identify complementary resources (tangible and intangible) and to subsequently integrate, transform and use them for the creation of competitive advantage – a process just recently associated in tourism research with the concepts of absorptive capacity (ACAP) or (synonymous) discovery capability. The few available integrative studies on this subject (Ozseker, 2018; Trunfio et al., 2019) indicate that ACAP is closely connected to organisational learning and innovation – a major source of competitive advantage at a cluster level (cmp. Porter, 2008; Roberts et al., 2012; Schuhbert, 2018). Innovations in turn are known to favor the emergence of new externalities and complementarities at the regional or national level and therefore provide a major mechanism for the intensification of existing and activation of new cross-sectoral linkages in the cluster system (Lejarraja & Walkenhorst, 2007; Martinez-Ros et al, 2009; Thomas & Wood, 2015; Isckia et al., 2018; cmp. also Roberts et al., 2012). This qualifies ACAP as a primary factor of cluster maturity and economic diversification.

As already mentioned, the absorptive capacity of a tourism cluster is not only a determinant of linkage formation and diversification but is also dependent on it. This circular causality is a typical paradox found in emergent phenomena (Schuhbert, 2013; Thomas & Wood, 2015). The question of how tourism routes can promote the maturation of a national cluster system here consequently depends not only on supplementing regional with transnational linkages (see mature stage in 2.1.), but also on how these linkages or networks of value-creating exchange relations are configured (Lasuen, 1973; Raich, 2006; Dörry, 2009; Baggio et al.; 2010; Schuhbert, 2013). This especially concerns their suitability for creating social capital within the destination (Trunfio & Campana, 2019).

Here, densely-knit strategic networks with a large and heterogeneous pool of private and public actors cooperating with a high level of trust and familiarity, with a mix of strong and weak or formalized and informalized linkages of reciprocal partner investments accompanied by low to medium power asymmetries (mediated through coordinating hub organizations or platforms), decentralized innovation activities and normative governance patterns are considered to provide the most favorable configuration (scale-free configuration) to support high levels of ACAP. The rationale lies in their intensive negotiation and communication processes, as in their encouragement of communities of practice (Raich, 2006; Baggio, 2010; Thomas & Wood, 2015; Schuhbert, 2018; Ozseker, 2018; Trunfio & Campana, 2019). The latter are broadly discussed as primary processors for social integration and transformation of knowledge and consequently for organizational learning and innovation activities at the network and the firm level (Dias Sequeira et al., 2011). In addition, the coexistence of weak and strong ties supports the (e)merging of diverse mental models, while coordinating hub or (ICT-based) platform organizations in the network support the transition of new knowledge into marketable innovation (Gretzel et al., 2015; Schuhbert, 2018).

Table 2:

Linear Regression between five GLOBE-dimensions of national and organizational culture (2004) and selected findings from the GCR (2015), n=58 GLOBE partner countries (incl. 20 BRI participants)

Predictors (GLOBE)

Dependant Variables (GCR)

Innovation (R²=0,669)

Value Chain Breadth

(R²=0,476)

State of Cluster Development

(R²=0,447)

Collectivism II Societal Practices (In-group Collectivism)

-,430

-,522

-,251

Future Orientation Societal Practices

,356

,503

,546

Power Distance Societal Practices

n.a.

,270

n.a.

Collectivism I Societal Practices (Institutional Collectivism)

,313

n.a.

n.a.

Humane Orientation Societal Practices

-,216

n.a.

n.a.

For the firm level, studies have shown the central role of management practices and human capital for ACAP in the tourism business. Individual executives’ mentalities and capabilities have been identified as important triggers for the transfer of mostly tacit market knowledge from multiple external sources through highly personalized, informal channels into internal exploitation processes (Hjalager, 2010; Thomas & Wood, 2014; Trunfio & Campana, 2019). Few key managers therefore serve as structural bridges or relays between outbound and inbound knowledge absorption processes. Overly centralized decision making, a low level of experience and an insufficient outbound/inbound connection of key managers can negatively influence ACAP and innovativeness at the firm and consequently also at the network level (cmp. Matzler et al. 2005).

The disposition to acquire, share and apply new knowledge, however, is not only a function of organizational structure and individual attitudes but also a quality of the corporate culture (Dias Sequeira et al., 2011). Here, various studies underline the strong anchoring of the ACAP in the organizational culture of firms and networks (cmp. Hjalager, 2010; Thomas & Wood, 2015; Trunfio & Campana, 2019), which serves as a repository and operating system for the absorption of new knowledge (“knowledge base”). Of particular importance here are the culture-based path dependencies, which only allow the absorption of the kind of knowledge that is compatible with the one already existing in the knowledge base (Roberts et al, 2012). Cultural similarity therefore qualifies as a major enabling factor for ACAP (Schuhbert, 2018).

Studies indicate that the mostly SME-dominated tourism industries in the IC and DC, besides their inherent disadvantages due to size (Baggio et al, 2010), are often culturally characterized by a lack of outward strategic, collaborative and entrepreneurial orientation (Pechlaner, 2003: 23–24; Raich, 2006; Baggio, 2010; Hjalager, 2010). This cultural disposition can have a negative effect on their ACAP, especially when it comes to the adoption of “highly technical formal knowledge” (Thomas & Wood, 2015). Consequently, this limits proactiveness, risk propensity and innovativeness in the tourism sector and the activation/intensification of cross-sectoral linkages with a detrimental effect on diversification (Matzler et al, 2005; Hjalager, 2010).

Results from the 2004 study of the “Global Leadership and Organizational Behavior Effectiveness Research Program” (GLOBE) on national- and organizational-cultural dimensions in a total of 59 countries empirically highlight this close relationship between cultural disposition, innovation, linkage creation and cluster development. Building on a set of nine individual, theory-based dimensions, a series of 17,370 comprehensive quantitative interviews was realized between 1994 and 1997 with middle managers from 951 local companies from the food processing, financial services and telecommunication industries1 to identify distinctive patterns at the levels of national and organizational culture2 including aspects of leadership. The results were matched with the findings of the annual “Global Competitiveness Report” (GCR), issued by the World Economic Forum, which frequently measures the state of innovation, breadth of value chains, cluster development and more for about 140 countries (cmp. Kutschker& Schmid, 2008, 743).

Tab. 2 shows linear regression modeling3 of the two studies with the GLOBE dimensions as predictors and the respective GCR indicators as dependent variables. The results point to the substantial role of five GLOBE culture dimensions in the explanation of innovativeness, linkage creation and cluster development in the 58 countries participating in both the GLOBE and GCR assessments4. Accordingly, In-group Collectivism or “the degree to which individuals express […] pride, loyalty, and cohesiveness in their organizations or families” generally exerts a rather detrimental effect especially on innovation and linkage creation, while Institutional Collectivism or “the degree to which organizational and societal institutional practices encourage and reward […] collective distribution of resources and collective action” is generally conducive to innovation5. The same applies to “the extent to which individuals engage […] in future-oriented behaviors such as planning, investing in the future, and delaying gratification,” here referred to as Future Orientation, which also seems to be a considerable contributor to linkage and cluster development. Finally, “the extent to which the community accepts and endorses authority, power differences, and status privileges” or the Power Distance is shown to exert a positive effect on value-chain creation in the 58 countries of the study sample.

The circular-causal dynamics of the abovementioned factors qualify cluster maturity as a complex emergent phenomenon whose effect on economic diversification pays out as a synergetical structure of factors that“is more than the sum of its parts” (Porter, 2008; cmp. Trunfio & Campana, 2019). This makes it harder to evaluate possible effects of tourism routes on cluster system maturation. As literature generally emphasizes the innovation potential inherent in the process of experience co-creation and cross-cultural identity creation of (trans) national tourism routes (Zabbini, 2012; Trunfio & Campana, 2019), the NSR could positively contribute to a self-reinforcing stimulation of network building, ACAP as well as cultural and structural change in the DC destinations.

2.4 The Role of Moderating Factors

Besides the aforementioned structural, relational and cultural factors, cluster-system maturation is also dependent on a set of framework conditions or moderating factors (Capone et al., 2016). A minimum level of socioeconomic development, sophistication of tourist demand (see 2.1.) and institutional incubatory power is thus required for the activation and intensification of linkages between tourism and related industries as a starting point for any diversification process (Lejarraja & Walkenhorst, 2007; Hjalager, 2010; Sannassee et al., 2014; De Vita & Kyaw, 2017).

The effectiveness of public institutions and policies in the establishment of mature regional and national cluster systems shows itself on the one hand in concerted support measures for entrepreneurship (e. g. through the promotion of competition, a human capital-friendly education and training policy, labor market regulation, a cost-effective regulatory and legal system, security/stability and infrastructure development). On the other hand, there is a need to manage conflicts and dissolve barriers to cross-sectoral cooperation among public and private stakeholders through an orchestration of knowledge flows on undiscovered interdependancies or complementarities, stimulation and coordination of relationships and ongoing institutionalization of cooperation by supporting negotiations, network- and knowledge management, engaging hybrid modes of dynamic stakeholder-participation (Raich, 2006; Moric, 2013; Thomas & Wood, 2015; Ozseker, 2018; Trunfio & Campana, 2019). Cooperation and rivalry form a field of tension for the emergence of social capital (Hjalager, 2010).

Hence, an important group of factors concerns the business environment. As the maturation requires rising levels of allocation efficiency with concurrently rising transaction complexity, the efficiency of the finance sector in providing investment capital for innovation or entrepreneurial activities of SME is a critical factor for tourism cluster system development in the DC (Schuhbert, 2013). This is especially true since public funding and investment policies in many DC are highly localized and selective and contribute to the above-mentioned instability of rural regions in the DC (see 2.1. and Vorlaufer, 1996, 109, 172–178 et sqq.; Letzner, 2010: 166; Schuhbert, 2018, 236). In this context, trade policy also has a major influence on linkage creation and diversification. Thus, recent studies imply that open trade policies are more conducive to tourism-induced (export) diversification than a restriction to isolationist import-substitution policies (Lejarraja & Walkenhorst, 2007).

Building on the factor-channeling function of tourism routes (2.2.), an improved disposition and allocation of investment capital (e. g. through foreign direct investments), market dynamics and trade liberalization could be positive side effects in the context of the NSR.

2.5 Conception of an Analytical Framework

The conception of (transnational) tourist routes as systems of interconnected clusters is a fairly new approach in destination research. Following the explorative, holistic design of this study, a first model of the conceptual framework to assess the research question can have be started by further bundling, categorizing and organizing the selected key concepts discussed in the previous sections. The search for a synthesis follows the concept of an integrative literature review – a frequently applied method in tourism research for emerging topics (Trunfio & Campana, 2019). The results can be taken from Fig. 1.

The framework condenses the findings on the structure and dynamics of a tourism cluster system in a set of seven factors that can be aligned with a total of three main categories of determinants for cluster maturity. Building on the conception of mature tourism clusters as destinations with a sustainable competitive advantage based on innovation (see 2.3), these categories reflect key determinants of destination competitiveness (see Raich, 2006, 159, 260).

This concept shows considerable overlap with existing approaches to model cluster maturity. One example worth mentioning here is the approach of Ketels et al.(2006, 16), who identified the above-mentioned seven factors in the course of their global, quantitative online survey on cluster initiatives in DC as main elements of cluster maturity (cmp. Schuhbert, 2013, 148 et sqq.). Related findings were also produced by research on (tourism) innovation systems and ecosystems (Hjalager, 2010; Roberts et al., 2012; Gretzel et al., 2015; Isckia et al., 2018).

For the sake of conceptual clarity, Fig. 1 also displays the further methodological case-based approach, which shall be discussed below.

3 Methods

Keeping the study goals in mind, the presented findings provide a sound theoretical basis for an explorative assessment of the question whether the cluster system of Azerbaijan as an NSR partner country is mature enough to effectively use an embedded transnational cultural tourist route for economic development. Building upon Hjalagers (2010) methodological observations on innovation research, a mix of quantitative and qualitative methods shall be applied to the analysis of the factors described in section 2 (see Fig. 1).

Quantitative approaches are widespread in tourism and non-tourism literature when it comes to assessing the static and dynamic dimensions of regional clusters (no. 1–2) and sectoral clusters (no. 3–5) or their maturity as described respectively in section 2. This concerns:

  1. No.1.The stability of spatial hierarchies (see 2.1.): This has been assessed by Lasuen (1969) on the basis of time-series census data on urban population ranks, correlated with an initial value in order to trace the dynamics of urban hierarchies. For a respective assessment in this study, census data are available for the years 2000–2017.
  2. No.2.agglomerations of settlements and tourist infrastructure (see 2.1.): As a relatively close spatial coupling of the tourist infrastructure (here: accommodations only) to the settlement structure is expected for the sample country, an assessment can be done by means of relative distance measurements with the urban structure. The description is strongly linked to the data from no. 3 and supported by the qualitative statements (s.b.).
  3. No.3.level of competitive pressure (see 2.1.): This has been measured in the literature on tourism clusters (Schuhbert, 2013) through a descriptive analysis of primary statistical market data (here: from the Azerbaijan Statistical Committee, AzStat). Stakeholder perception and strategic evaluation on competitive pressure are subject to qualitative assessments.
  4. No.4.economic diversification levels (see 2.1): Used as a dependent variable in econometric model-building, this variable is frequently operationalized via the inverse of the Herfindahl Index to measure product and export diversification (see Lejarraja & Walkenhorst, 2007; Sannassee et al. 2014). As available statistical data do not allow a detailed analysis at the product level, this study applies the inverse of the Herfindahl Index to measure the distribution of companies per capita in six tourism-related industries (agriculture, trade, manufacturing, construction, accommodation and catering) for 55 regions in the sample countryand for the years between 2013 and 2017.
  5. No.5.configuration of linkages (see 2.3): This reflects the degree of cross-sectoral networking among sectoral stakeholders. While the perspective of interorganizational and spatial relationships is increasingly being explored through the use of sociometric network analysis (Baggio et al., 2010; Asero et al., 2015), the value-chain perspective is often viewed through input-output analysis (Lejarraja & Walkenhorst, 2007). For this study, both approaches are combined, since this allows us to infer from the structural characteristics of social relationships (here: exchange of goods and services in a valuechain) to internal functionalities of these systems. To this end, a series of key figures has proven to behelpful for the analysis of sectoral cluster dynamics. For the purpose of this study, connectivity and density measures are applied in particular to determine whether a given network configuration is theoretically in line with the ACAP-optimal (scale-free) configuration (see 2.3.) and therefore conducive to innovation (Baggio et al., 2010; 2015).
Fig. 1:
Fig. 1:

Analytical Framework of the Study; level of reference: I = international, N= national, R = regional

Citation: Zeitschrift für Wirtschaftsgeographie 64, 4; 10.1515/zfw-2019-0021

For the study of the moderating and dynamic factors of cluster maturation, in particular for the consideration of ACAP, organizational culture and network/linkage dynamics, quantitative approaches can also be applied (Thomas & Wood, 2015; Matzler et al., 2005; Baggio, 2010; WEF, 2018). However, since these approaches have limitations when applied to tourism and social dynamics, qualitative methods are preferred in the literature (Hjalager, 2010; Schuhbert, 2013; Thomas & Wood, 2015). This applies in particular since studies show that the above-mentioned factors and the level of socioeconomic development are not only interdependent but circularly/dynamically causal or nonlinear in nature, which would alternatively require complex simultaneous equation modeling for quantitative assessments (Xinhua, 2008; Hjalager, 2010; Schuhbert, 2013; Thomas & Wood, 2015; De Vita &Kyaw, 2017).

For this reason, the three main categories from section 2.5. shall serve as very general analytical containers for explorative nets of semantic associations, which are to be identified in the course of a Gabek coherence analysis (see Zelger, 2003; Pechlaner & Volgger, 2012) on 200 pages of transcripts from 24 extensive expert interviews (a total of 2,168 terms were coded in 1,427 sentences). The advantage of this method lies in the fact that central sense-structures can be made visible in the patterns of perception associated with the phenomenon of the NSR and related phenomena. The interviews were completed in 2017 and 2018 in the sample region of Azerbaijan (see below) with national and international representatives from the fields of accommodation, tour operation, culture, education and tourism governance selected on the criteria of maximum variance with the support of snowball selection.

The semi-standardized guideline concept was split into two parts: while Part I focused on the practical dimensions of the NSR initiative in its implications for cluster system development (e. g. competition, cooperation, financial capacities, political factors etc.), Part II primarily addressed the specifics of national and organizational cultures in its repercussions on ACAP and innovation. To this end, questioning in Part II adapted major concepts from the 2004 GLOBE study for qualitative use. This especially concerns questions about the cultural dimensions of “Collectivism,” “Future Orientation” and “Power Distance,” which demonstrably have a high impact on innovation, linkage creation and cluster development (see Tab. 2).

As this two-sided design increases the scope of associations, it also increases the opportunity to identify semantic connections within and between the seven determining factors of cluster maturity identified in Fig. 1. In particular, it allows us to appreciate the special role of cultural tourist routes as transnational pipelines for knowledge and ideas through the analysis of semantic connections between the practical dimensions of the NSR and given cultural dispositions of the sample country and related NSR partner countries.

Case Selection and Description

For the discussion of the research question, the case of Azerbaijan was chosen from the list of NSR partner countries, which have been classified as either Lower or Upper Middle Income Countries (cmp. 2.1.) through the World Bank Atlas Method (N=20). The spatio-economic structure of the South Caucasian Country is still strongly oriented on the oil industry and its exports (primarily located within the Baku Metropolitan Area, BMA), although the importance and scope of non-oil industries are constantly growing as a result of the State Development Programs of the past 15 years (Karimov, 2015, 44–49). Objectives of the latest program focus on upgrading and linking production processes of several key export industries such as mining, construction, logistics, manufacturing and tourism with the goal of keeping higher rated, value-creating functions in the country and especially in the peripheral regions. The creation of specialized regional-sectoral clusters in peripheral zones (“Economic Regions”) is an integral part of Azerbaijan’s economic development strategy (Karimov, 2015, 45–51; Schuhbert, 2018, 234–236). In terms of infrastructure projects, Azerbaijan offers the Baku-Tbilisi-Kars Railway (BTK), the South-North highway and the Alat International Sea Trade Port south of Baku, with a considerable contribution to the BRI (Azernews 2019e). The BTK was constructed between 2008 and 2018 on the basis of an Azerbaijani-Georgian-Turkish cooperation with an estimated capacity of one million passengers and 6.5 million tons of freight per year (Azernews 2019d; Belt and Road News 2019).

The political attitude in Azerbaijan towards the BRI is supportive, which is shown by numerous infrastructure projects and agreements (Valiyev, 2015). Nevertheless, the trade balance is still uneven: Deliveries of Chinese products are many times higher than Azerbaijani exports to China, which also calls for increased local production and entrepreneurship (Belt and Road News, 2019). The trade turnover from January to September 2019 reached $1.7 billion, which is 96 percent more than in the same period in 2018 (Azernews, 2019a). China has thus become one of the most important trading partners with increasing numbers every year. The Foreign Direct Invests also reached a peak, as Chinese enterprises invested $800 million in the Azerbaijani economy. Although the Azerbaijani investments in China remain marginal (Azernews, 2019e), Azerbaijan became a founder of the Asian Infrastructure Investment Bank in 2015 (Belt and Road Portal, 2018).

As projects like the BTK show, the BRI does not only have a bilateral perspective, instead the transnational cooperation of neighboring countries becomes a key element for a successful Trans-Caspian transport corridor (Pechlaner et al., 2019). As the countries like Georgia and Azerbaijan in the South Caucasus and the Central Asian countries share an interest in creating a competitive corridor, they engage in projects, such as the Trans-Caspian International Transport Route agreement (TITR) and TRACECA (Transport Corridor Europe-Caucasus-Asia 1993–2007) or CAREC (Central Asia Regional Economic Cooperation Program) (Emerson et al. 2019, 6–10). Further initiatives strengthen the European-Caucasus connection, e. g. through the development of the Extended Trans-European Transport Network, TENT (European Commission 2019), or the connection to Afghanistan through the Lapis Lazuli transit route, which is funded by the Asian Development Bank (The Economic Times, 2018). An international conference, “TRACECA – Restoration of the Historic Silk Route,” already took place in Baku in 1998 and proposed to reactivate the ASR (Azernews 2019b).BMA is all the more considered as an important hub, which is also supported by committee meetings for the intensified container service along the Trans-Caspian Route. However, the still difficult political relations between some countries hinder this development (Valiyev, 2015) and the effects of the 2020 worldwide Coronavirus Crisis can not yet be estimated.

In the case of tourism, the rationale for selecting Azerbaijan as a sample is based on the fact that Azerbaijan is currently a part of initiatives that aim for the establishment of a transnational cultural tourism route (such as the “Modern Silk Road Route,” MSRR, by the Council of Turkish Speaking Countries or the UNWTO Silk Road Program). To date, incoming tourism is strongly concentrated on the BMA, with business and culture/sightseeing as the most important activities by far (Arnegger& Mayer, 2015, 32). Domestic tourism, on the one hand, is geographically and thematically more spread out and (in addition to the high importance of cultural tourism) also focuses on nature tourism (for details, see Schuhbert, 2018, 252–254). On the other hand, the rankings of the Global Competitiveness Index (GCI) by the World Economic Forum (WEF, 2018) provide further support for the economic description:

Accordingly, Azerbaijan is highest ranked among the sub-group of Caucasian and Central Asian partner countries when it comes to institutional strength, the market efficiency of labor and goods, technological readiness, innovative capacity, breadth of value-chains, state of cluster development and local supplier quality. It is also among the top 5 of the total group in these respects.When it comes to cluster development, Azerbaijan outranks all neighboring countries in the region except Turkey and Iran. On the other hand, local supplier quantity (11th of 20), macroeconomic environment (9th of 20), financial system depth (12th of 20), education and training (9th of 20) and tourism competitiveness (10th of 20) are only at a very moderate level. This qualifies the country as an excellent sample case for the investigation of cluster-system development in the context of cultural tourist routes and as a potential role model for similarly structured DC in the region that share the historical connection to the ASR and strive for inclusion in the NSR.

In this regard, a major advantage of the Azerbaijani case is the close geographical proximity of the existing regional tourism destinations to the course of the ASR and NSR (see Fig. 2). As this basic structure can also be found in neighboring NSR partner countries (e. g. Kazakhstan, Kyrgyzstan, Turkmenistan, Iran) in congruence with similarly high levels of general urbanization (cmp. Henderson et al., 2018), this makes the embedding of transnational cultural tourist routes(such as the MSRR) all the easier and therefore might allow a (partial) transfer of this study’s findings on those cases.

4 Analysis

4.1 Static Spatio-Structural Analysis of Industries

4.1.1 Geographical Clusters

When it comes to the number of acting enterprises in industry and service, the economic center of Azerbaijan is Baku, followed by secondary economic centers in Sumgait, Mingachevir or Ganja (AzStat, 2019). Overall, the spatial structure of Azerbaijan is clearly characterized by the allocation of all kinds of social and economic activities (including tourism) around the capital Baku, while Sumgait and the related Absheron region benefit from the geographical proximity to the capital (hereafter referred to as Baku Metropolitan Area, BMA). Nevertheless, Azerbaijan is strongly shaped by smaller settlements and a dynamic development in the east. The population numbers provide an explanation of the stability of the Azerbaijani hierarchy in urban centers. During the last 17 years (range of available data on a regional scale), the ten biggest cities (Tab.3) have seen steady growth and rarely changed in their ranking order. The correlation between these urban rankings, which Lasuen (1969) has applied to study the stability of spatial distribution in major cities, shows significant values for Azerbaijan between .937 and .999 (Spearman-rho), although the value is slowly declining. Consequently Azerbaijan shows a stable hierarchy in its urban development scheme, although slight differences have become evident lately, whose informative value is limited due to the short data row.

The available statistical data (Tab.4) on overnight stays, income generated by hotels and the hotel land register show a hierarchy in destinations based on the country’s nine economic regions. Supplementary to every region, Tab. 4 and Fig. 2 show the touristic hotspots at the rayon level. Four out of ten economic regions are listed below with a high relevance for tourism in general and the NSR or MSRR in particular, while the other six regions show weaker statistics in touristic supply and demand. The Absheron economic region, which is represented by the BMA, offers the strongest numbers in tourism and is therefore the touristic center in Azerbaijan – also due to its allocation of infrastructure, such as airport and railway, as well as its sophisticated business services and labor supply (cmp. functions of primate cities in section 2). In contrast to Baku, the further destinations are driven by more rural characteristics: Guba-Khachmaz, Sheki-Zaqatala and Ganja-Gazakh. Selected regions beyond these that are worth mentioning in a touristic context are Lankaran town, Masally town and Shamakhi region,which also provide a decent number of hotels.

Table 3:

Population statistics, cities and urban population in Azerbaijan 2017, in Thd. Source: Az Stat (2019)

Baku

Sumgayit

Ganja

Absheron

Mingechevir

Lankaran

Shirvan

Nakchivan

Shamkir

Yevlakh

2245,8

339

331,4

170,5

103,2

87,8

85

81,8

73,8

68,4

Table 4:

Statistics on tourism in economic regions

Related Districts

Population

(including growth rate between 2000 and

2017 in %)

Hotel Land Register, Number of Hotel

Overnight Stays

(including growth rate between 2006 and

2017 in %)

Income of Hotels and similar Accomodation in Tsd. Manat

AzStat (2017)

Ministry of Tourism (2017)

AzStat (2017)

AzStat (2017)

Economic Region 1: Absheron

2.808,9

(+27,9 %)

160

1.598.507

(+129,2 %)

218.543,8

Sumgayit Town, Khyzi, Absheron, Jalilabad Region

Baku City

2.245,8 (+24,3 %)

149

1.579.679 (+129,7 %)

216.879,1

Economic Region 2: Guba-Xachmaz

538,8

(+20,97 %)

51

311.502

(+111,1 %)

19.935,7

Shabran, Siyazan Region

Xachmaz (incl. Nabran)

174,8 (+20,1 %)

32

129.102 (+18,3 %)

5.099,0

Guba

168,4 (+20,1 %)

10

79.235 (+857,6 %)

2.686,0

Gusar

96,2 (+17,6 %)

9

101.581 (+1.083,4 %)

12.048,7

Economic Region 3: Sheki-Zaqatala

611,9

(+16,8 %)

35

247.793

(+909,7 %)

19.688,7

Balakan, Gakh, Oguz

Sheki Town

184,2 (+16,1 %)

11

11.822 (+81,6 %)

1.043,5

Gabala Region

104,4 (+24,1 %)

7

209.903 (+13.583,4 %)

17.156,6

Zaqatala

126,9 (+17,2 %)

6

7.062 (+186,1 %)

389,9

Economic Region 4: Ganja-Gazakh

1.265,2

(+15,8 %)

29

170.580

(+111,0 %)

12.330,4

Gazakh, Agstafa, Tovuz, Shamkir, Gadabey, Dashkesen, Samukh, Goygol, Goranboy Region

Ganja Town

331,4 (+10,2 %)

10

35.551 (+154,9 %)

2.689,4

Building on this, a location-based analysis of the hotels in the related cities has been conducted with data provided by the Ministry of Tourism. The distribution of hotels within the designated destinations confirms a close relation to the settlement structure, while there are certain spots in nature-based tourism outside of the cities, e. g. Shahdag in mountain tourism, Xacmaz in seaside tourism or hotels along the rivers surrounding Sheki or Gabala. The location-based analysis has therefore proven the development of some geographically proximate clusters that start evolving specialized tourism segments apart from the nationwide dominating culture and business tourism segments (Schuhbert, 2018).

4.1.2 Sectoral Clusters

A destination or tourism cluster evolves through a range of services along the touristic value system, which evolves to a great extent around a nucleus of core service providers (cmp. Andersson et al., 2004; Ketels et al, 2006; Ozseker, 2018), such as hotels and transport companies. But it also depends on supply industries, such as intermediaries, institutions for collaborations, handicraft, construction or nutrition. Additional supply-related markets are energy, health, ICT or finance (Schuhbert, 2013, 161 et sqq.; Trunfio & Campana, 2019).

Based on this understanding of tourism-related industries, the Herfindahl Inverse was calculated for the Azerbaijani hospitality industry and 5 related supplier industries (see section 3) on a rayon basis. Accordingly, Fig. 2 shows the spatial localization of the Azerbaijani rayons with reference to their current level of industrial diversification, main infrastructures related to the BRI/NSR projects and the different destination hierarchies, respectively. A striking aspect is the pronounced geographical matching of the more diversified regions with the country’s tourist hotspots (see section 5).

Fig. 2:
Fig. 2:

Map

Citation: Zeitschrift für Wirtschaftsgeographie 64, 4; 10.1515/zfw-2019-0021

Further light on existing interrelations between tourism and related industries can be shed when analyzing the existing degree of value-chain related networking in the Azerbaijani economy.

Table 5 shows the results of a sociometric network analysis, created for this study on the basis of the latest edition of input-output tables available at AzStat (2011). The hierarchy of nodes (industries) and edges (input and output processes), visible in size and color shade in Fig. 3, highlights the connectivity of the 81 respective industries in the Azerbaijani economic system. Based on the weighted degree, which measures the totality of input-oriented (indegree) and output-oriented (outdegree) productive relationships (cmp. Baggio, 2010), the industries with the highest level of connectivity are indeed construction, land transport and wholesale/retail trade, with accommodations still ranked among the top ten.

Fig. 3:
Fig. 3:

Network of value creation processes of 81 Azerbaijani industries in 2011 based on “weighed degree”

Citation: Zeitschrift für Wirtschaftsgeographie 64, 4; 10.1515/zfw-2019-0021

Table. 5:

Key I/O – network indicators

Sociometric Industry-Network Indicators of the Azerbaijani Economy

Average Degree

22,62

Edge Density (directed)

0,286

Av. Authority (directed)

0,096

Modularity

0,107

Av. Clustering Coefficient (directed)

0,499

Av. Hub (directed)

0,093

Sociometric-Network Indicators of Selected Tourism Industries

Indicator/Industry

Accommodation

Travel Agency, Tour Operator, Reservation Service and Related Activities

Air Transport

Land Transport and Trandport via Pipelines

Weighted Indegree

(Rank/81 Industries)

73 (13/81)

30 (40/81)

46 (25/81)

81 (9/81)

Weighted Outdegree

(Rank/81 Industries)

66 (12/81)

9 (65/81)

18 (52/81)

128 (1/81)

Weighted Degree

(Rank/81 Industries)

139 (9/81)

39 (57/81)

64 (37/81)

209 (2/81)

Eigencentrality

(Rank/81 Industries)

0,80 (8/81)

0,42 (34/81)

0,43 (32/81)

0,76 (9/81)

Clustering Coefficient

(Rank/81 Industries)

0,40 (68/81)

0,58 (18/81)

0,51 (38/81)

0,35 (76/81)

Density of Ego-Network (directed)

0,417

0,608

0,536

0,364

Economic Indicators (Value created on Networks of Selected Tourism Industries)

Value Added

(Rank/81 Industries)

186.553.256 AZN

(22/81)

70.414.905 AZN

(33/81)

275.102.477 AZN

(18/81)

2.138.535.193 AZN (5/81)

A closer look at the four core tourism industries (see Tab.5) additionally reveals a generally moderate density of input-output linkages. With regard to the value of transactions, Azerbaijan’s accommodation industry is best connected on the input side, with national food producers, electricity and gas providers, land transport and real estate activities, while serving as an output supplier for wholesale and retail trade, construction, public administration and human health activities. The travel agency and tour operator industry on the other hand show a fairly limited transaction volume.

The total network itself is finally to be characterized by a rather low to moderate level of density (directed: 0.286; undirected: 0.457). A rather high clustering coefficient points to the presence of industrial communities (most probably concentrated in the BMA, see above), which is supported by modularity measures (at least three communities are present). However, the fairly low values for hub and authority, which measure the prominence and link-quality of actors in the network, indicate the absence of a clear scale-free, strategic configuration (see 2.3.). Instead, a structure of relatively isolated sub-clusters prevails. In total, this implies a coexistence of conducive and detrimental factors in cluster maturity.

4.2 Analysis of Cluster Dynamics

The above static perception covers only the temporary manifestation of the past maturation process. As the clash of competitive pressure and cooperativeness is a main catalyzer for the long-term development of cluster maturity (see section 2), this section now appreciates the dynamic perspective. Fig. 4 displays the results of the GABEK analysis performed on the interview materials discussed in section 3. Based on the strength of semantic associations connected to start terms representing the primary factors for the maturity of a destination system, a set of sub-groups or categories was formed as containers for the following condensation and discussion of major findings from the interview campaign (cmp. Fig. 1).

4.2.1 Competitive Dynamics of the Destination System

In accordance with the quantitative findings presented in section 4.1.1 and Tab. 43, the experts noticed a substantial growth in demand over the past few years. With the prospected shift of the pleasure periphery from Eastern and Western outgoing tourism markets towards the Caucasus, further growth momentum is expected here, especially in the nature, agricultural, wellness and cruise tourism segments that are seen as primary profiteers of the NSR and adjoined projects.

Due to the progressive differentiation of tourism markets and the continuing overcompensation of supply through growing demand (for example in the premium hotel industry), rather low to moderate competitive pressure is described for most segments of the Azerbaijani tourism sector (and especially within and between the regions), resulting in pricing advantages on the part of hotels and only a moderate level of quality- and innovation-based competition: “additionally, having 1–2 star budget hotels can improve the competition. Because, other hotels also will decrease the prices and it will ensure the competition. What can be the sign of the competition? Only the high level of service. […] So, there is always competition, it will increase if there is a will to construct new hotels” (J62).

As neither cooperation nor hard confrontation dominates the strategic behavior of Azerbaijani tourism companies, a“friendly rivalry” (O51) perhaps best summarizes the current state of competitive dynamics in the Azerbaijani destination system, with loose regional and national network relations limiting the scope for collaborative efforts. As interdependancies or complementarities are only scarcely discovered by tourism companies (Schuhbert, 2018), a “healthy competition”(M09) between the various regions of Azerbaijan is described as necessary to break up existing individual egoisms and to boost networking. The same goes for the regulation of prices, standardization of service quality as well as the setup of entrepreneurial activity margins as a means to finally promote the diversification of Azerbaijan and other NSR partner countries to the inside and the outside. It is expected that rising interregional competition and the accelerated transfer of goods, factors of production and service standards within the framework of the NSR will reduce purchase prices, increase the entrepreneurial scope and accelerate development in the regions in the long term.

This should be achieved on the one hand through increased incentives for capital investment and on the other hand by creating employment in regional tourism as well as agricultural, arts and crafts businesses; here especially in silk production (cmp. Karimov, 2015). Associations and government interventions are expected here to become increasingly important in order to effectively balance cooperation and rivalry (e. g. by setting stimuli for cheaper accommodation segments), to stabilize the macro-environment (see section 3), to coordinate prices and to reduce barriers for cooperation (see 2.4.). At the regional level, this applies to public and private DMCs and at the transnational level to international organizations (e. g. UNWTO, Turkic Council).

Fig. 4:
Fig. 4:

GABEK Network of Associations on Key Category Terms

Citation: Zeitschrift für Wirtschaftsgeographie 64, 4; 10.1515/zfw-2019-0021

4.2.2 Composition and Competence of Partners in Value Chain Networks

Cooperation is generally described as a basic prerequisite for development and here the NSR is seen as an enabling infrastructure for the exchange, collaboration and further linkage of products or destinations to the inside and the outside for the sake of further economic diversification:“Because the better connections we have with these countries, the better chances we have to establish different economical types” (D31).

Some experts describe a lack of professional cooperation at all geographical levels (regional, national, international) as a serious problem in Azerbaijan’s past and present tourism. However, various interview partners noticed a recent change of mind towards the role of collaboration and association among private tourism SME: “[…]in different parts of the country, there are small entrepreneurs which try to share and just always say that we are doing this, we are doing that because they also want to be part of this great change. And I believe that within the country we are ready to cooperate now and this is very important” (E16).

National and foreign tour operators and agencies currently play a vital role here as network facilitators:“These types of tour operators are very active and mostly being in the center of this exchange, they are gathering evening meetings, evenings for tourism educators, for example” (K56). However, experts state that increasing cooperativeness to the inside and to the outside also requires impulses and support from the above-mentioned national and international public tourism entities (e. g. through common vision, network facilitation, concerted marketing and branding strategies/initiatives, market research and consulting, standardization, investment funds for attractions, etc.). Here a special challenge lies in the facilitation of knowledge exchange and mutual learning among regional public and private tourism stakeholders for the purpose of improving market transparency and the bundling of tourism-related resources and products. For example, most of the influential tourism associations are not really present outside the BMA and existing regional DMCs are insufficiently linked with one another:“There are some information centers in different regions and they are somehow operating. But, also it would be wrong if we say there is no information between them” (O27).

Learning from foreign best practices through cultural encounters and exchanges of goods, people and ideas via trade is historically considered to be Azerbaijan’s central engine of socio-economic development and tourism is expected to be one of those sectors6 that will make the most effective use of the NSR for further network formation (cmp. 2.3.).

Nevertheless, some experts from the private sector observe a lack of capacity when it comes to the absorption of foreign expert knowledge, emphasizing an inadequate endowment with venture capital, insufficient access to best practice knowledge and a lack of awareness as major drivers for limited absorptive capacities at the regional level. When asked for the reasons, various experts saw connections with culture-bound path dependencies when they state:“it’s possible that their structure, model [of international experts] is not suitable for us. Their administrative system or mentality does not suit us”(P16) or even more pronounced:“I think the essential reason is mentality. Our mental states give us no opportunity. That’s why we cannot do it”(R12). This further points to cultural incompatibilities (see 2.3.) on the one hand and to a very ambivalent attitude towards organizational learning on the other hand:“Of course there are some people that are very open to trainings, all new information and all the new trends going on globally. They are kind to learn but there is also some people, they are unfortunately not interested in anything– just trying to earn some money”(G14). The absence of professional, ICT-based knowledge/information management as well as market research integrated within and between companies and public DMCs supports this notion. However, various experts have expressed strong enthusiasm about the opportunity for NSR-triggered intercultural learning on an organizational level (e. g. alignment of quality standards) and individual level (e. g. co-creation of cultural identities), where the cultural similarities between the partner countries are expected to serve as a supporting factor.

4.2.3 Entrepreneurial Orientation and Capacity of Destination Stakeholders

Facing only moderate competitive pressure and a limitation of absorptive capacities, major moderating factors for the absorption of knowledge and the subsequent realization of innovative potentials and entrepreneurial endeavors are in a suboptimal condition to increase diversification in the Azerbaijani tourism sector. However, the NSR is also broadly associated with the hope of a shift towards higher levels of innovativeness and entrepreneurship, as it offers a potential for social co-creation of experiences, which Trunfio & Campana, 2019 describe as a major source for destination innovativeness: 1. Co-creation of a post-Soviet identity for those transition countries in the Caucasus that have been externally dominated for centuries and 2. Co-Creation of a common experiential space which is about to radically broaden the scope of entrepreneurial activities:“Innovation is the vital factor in the development of tourism. If there are new innovations, the tourist will be involved” (J66).

As a result of the stronger focus on upgrades in service quality and prices, innovation activity is currently limited and predominantly of an incremental nature (e. g. structural extensions, new sports facilities and internet services such as mobile apps) with a regional scope (cmp. Hjalager, 2010). While incremental product/service innovations (e. g. hotel menus or free WiFi) are considered easy to create and used to spread rapidly across the regions of Azerbaijan, the reason for the lack of (radical) innovation is seen in the low availability of capital, lack of government support and specialized personnel. Location factors and the spatial concentration of economic activities in the Absheron region (see 4.1.) are also described as limiting development in general and innovation-oriented entrepreneurship in particular: “This [realization of risky innovative ideas] is a very good way for development, but us bothers the financial condition. […] That works very badly on our motivation” (T22). Although the Azerbaijani tourism industry can generally be characterized by optimism towards change, reasons for limited absorptive capacities are also grounded in negative attitudes towards the innovation process itself, which is described by some stakeholders as a “tough process”or even a “threat”(095).

Others point to cultural foundations of an inherent averseness to innovation by Azerbaijani SME: “When we see a good work or result, we do not think about how to make that effort. We only think about the result” (P18).

In the light of the substantial effect that Future Orientation generally exerts on innovativeness, linkage creation and cluster development within the scope of the GLOBE study (see Tab. 2.), it is remarkable that related start terms7 such as “planning,” “planning_beforehand,” or “future_plans” (see Fig. 4) are semantically only very weakly associated with concrete innovation projects and their realization, especially at the level of individual hotel operations, and that semantic connections to an external cooperation with other partners, network and linkage creation are practically missing completely. In several cases, a general appreciation of the long-term planning of innovation projects is observable in statements like this: “No, spontaneous development never happens. I think that’s impossible. Development is a result of our strategy. We strive for innovations, novelties and more” (O55). Depending on the scope of the problem or task in place, related meetings used to be planned and organized several days, weeks or even years in advance but it is frequently emphasized that the planning horizon is limited by the above-mentioned financial constraints and more immediate problem setting:“Honestly we were not that active during this period. Because of other personal problems and work we could not deal with a lot. We think of this novelties for another three or four months” (P90).

The totality of related associations and connected statements point to a mid-level expression of Future Orientation in Azerbaijan, which can be reflected by the regional context, as the neighboring countries of Turkey (3.74), Iran (3.70), Kazakhstan (3.57) and Georgia (3.41) display similar scores in the GLOBE ranking. Among the 20 BRI partner countries examined in the GLOBE study, Future Orientation reaches an average of 3.71 with a standard deviation of 0.49, indicating a rather homogenous situation among the BRI partners.

As Tab. 2. points to the genesis of value-creating linkages being a function of Power Distance, related start terms are “hierarchy,” “subordination,” or “criticism” (see Fig. 4), which are connected to “innovation” via its association with “decision_making.” Associations with linkage-related terms are basically limited to “idea exchange” or (to a limited extent) to “networking,” thus showing no direct indication of an awareness towards value-chain development (cmp. 4.2.2). Although some statements point to “a middle subordination”, “limited democracy” (T15) and level-crossing, open discussion of mistakes, ideas and opinions, a general consensus among tourism-related organizations or companies is to “promote high hierarchical structures” (T73), without acceptance of criticism while “keeping and treating everyone in integrity with hierarchy and also subordination” (S44) sustained with the help of “disciplinary procedures” (Q65). Top-down decision-making serves as an infrastructure to channel and select internal and external ideas into realizable projects, which has to be considered a first step towards linkage-creation (cmp. Lejarraja & Walkenhorst, 2007 and section 2.1). However, high Power Distance between employees and managers is sometimes expressed in the notion that employees and the local population do not freely engage in innovation processes due to personal fear: “It all depends on the creativity which is actually what is probably that we will have to explain to them. Just to show them how this creative approach might create additional revenues for them” (H44).

The totality of related associations and connected statements point to a highlevel of Power Distance in Azerbaijan, which can be reflected by the regional context, as the neighboring countries of Turkey (5.57), Iran (5.43), Kazakhstan (5.31), Georgia (5.22) and Russia (5.52) display similar scores in the GLOBE ranking. Among the 20 BRI partner countries examined in the GLOBE study, Future Orientation reaches an average of 5.11 with a standard deviation of 0.46, indicating a rather homogenous situation among the BRI-partners.

In-Group Collectivism, on the one hand, is expressed in strong associations between terms such as “employees,” “managers,” “group_meeting,” “relations,” or “employment time,” which in turn are interconnected with aspects of innovation and linkage networks only at a medium level (cmp. Tab. 2). Institutional Collectivism, on the other hand, is strongly reflected in “employee” – related aspects of “teamwork,” “motivation,” handling of “own_ goals,” and “incentives,” also displaying only a minor to medium association with “innovation” (cmp. Fig. 4).

In general, statements emphasize the high importance and presence of friendly, open and respectful collaboration in daily interactions at the level of individual Azerbaijani companies and between individual organizations engaged in the NSR initiatives. Individual statements however, describe emotional attachment, respect, motivation and commitment among employees and managers either as a function of employment time/experience, financial, leisure-based, reputational or moral incentives or as a function of hierarchical control (reflecting the rather strong associations with the Power Distance block in Fig. 4.).

In this regard, some statements underline the function of middle managers as role models for the successful alignment of employee behaviors and a strengthening of their emotional commitment to the company (cmp. 2.3): “It’s very crucial and it is very important for the motivation. I would like to tell one thing: attitude is infectious–you can have a good attitude and you will spread positive out and everyone will be positive. Just tell one thing negative and you will be a negative leader and you will get negative people around you”(S23).

Although many statements document a general appreciation and (incentive-based) stimulation of employee suggestions and the employees’ willingness to contribute their own ideas to product innovation processes, the scope of individual self-realization is apparently rather limited, since “close and successful teamwork”(T66) is seen as a major prerequisite for success. As a result, appreciation is primarily based on an employee’s “high work ability and work flexibility”(T91) as well as on “professionalism” (T68), which frequently collides with low qualification levels of the (mostly locally hired) staff8: “That depends also on the employees. But there are not many professional employees, that’s our big problem and a major hardship”(T10). Much effort is therefore invested in keeping collective action aligned with entrepreneurial goals and keeping deviant behaviors under control:“When I see that one worker does not communicate well with others and always claps, I finish working with him”(Q24). At the same time, many companies are reluctant to make investments (e. g. for training) in their personnel, due to high staff turnover rates, especially in the rural regions of Azerbaijan.

The totality of related associations and connected statements points to a relatively high level of In-Group and Institutional Collectivism in Azerbaijan, which can be reflected by the regional context, as the neighboring countries of Turkey (5.88/4.03), Iran (6.03/3.88), Kazakhstan (5.26/4.29), Georgia (6.19/4.03) and Russia (5.63/4.50) display similar scores in the GLOBE ranking. Among the 20 BRI partner countries examined in the GLOBE study, In-Group Collectivism reaches an average of 5.48 with a standard deviation of 0.68 and Institutional Collectivism an average of 4.32 with a standard deviation of 0.37, indicating a rather homogenous situation among the BRI-partners.

5 Conclusion

The purpose of this study was the analysis of the current state of cluster-system development in Azerbaijan under special consideration of the potential of the NSR for cluster maturation.

To this end, Azerbaijan’s existing national destination system was analyzed in a geographical and (cross-)sectoral dimension by using a set of static and dynamic indicators assessed in a mixed-method approach. As a result of combining qualitative and quantitative methods, it was possible for the first time to make the highly complex connections between tourist cluster development, innovation, diversification and economic development empirically more transparent for an NSR partner country. The respective findings of the analysis are condensed in Tab.6:

The findings paint the overall picture of a generally weak but stable tourist cluster system in Azerbaijan, which, as a whole as well as in its components, lacks the prerequisites for effectively forging complementary resources into synergies – where, however, the question arises for future research, in how far these national patterns find a self-similar reproduction within the regional clusters (see 2.1.).

The weakness of the system is not least a result of its cultural disposition, as the GABEK analysis points to rather high levels of In-Group Collectivism which have been identified as potentially detrimental to cluster development (see Tab. 2). As the results of the GLOBE study show, this is not uncommon for many countries in the region and confirms the relevance of many typical problem factors found in the literature in this regard. Overall, there is little evidence that the NSR is expected to work on these issues specifically. Many problems are addressed by the stakeholders without this reference.

Nevertheless, the GABEK analysis also shows that there exist more or less concrete expectations and mental models, constructing a connection between innovation, knowledge absorption, linkage creation, diversification, development and the NSR. As Fig. 4 shows, this concerns mostly the effect of moderating factors on competitive dynamics, visible for example in the prospected massive increase of tourist demand and the reduction of supply and factor costs through better infrastructure, but also in the promotion of the ACAP through intercultural exchange and the creation of linkage between tourism, manufacturing and primary industries (such as silk production). The above findings support the notion that Azerbaijan has a set of regional clusters in its national ecosystem which could profit from maturation impulses potentially provided through one of the planned NSR-related cultural tourist routes. The general and tourism-related growth dynamics in various small peripheral cities and regions in close spatial proximity to NSR key projects clearly point to this. However, the still huge spatial polarization on the BMA will only be compensated if the stakeholders manage to close the enormous structural gaps in the sectoral value-chain network. Due to its above-average connectivity (see 4.1.2), tourism could here bridge the gaps in a fragmented structure. The innovative potential required for this can be provided or at least strongly supported by the NSR, but this ultimately depends on specifically increasing absorptive capacities by promoting corporate entrepreneurial orientation, improving access to investment capital and establishing diverse strong and weak exchange relations within and between the existing regional sectoral clusters.

Table. 6:

Key Findings from the Analysis

Maturity of the Azerbaijani Destination-System

Geographical Clusters

Spatial Hierarchy and Stability

The hierarchy of the countries’ settlement structure has been quite stable over the past two decades

The accommodation infrastructure is geographically bound to the settlement structure as expected

Sectoral

Clusters

Diversification and Value-Chains

Diversification of key industries is currently at a low level in most regions of Azerbaijan (see generally high index-values)

Industrial diversification is but most pronounced in regions with tourism relevance such as Sheki, Gabala, Xachmaz and Ganja

Building of input-output linkages between key tourism- and other industries is (relatively seen) at a moderate to high level.

However, the rather low to medium density of the ego- and total network point a multitude of structural holes in the linkage net-work, which could indicate the existence of leakages (cmp. Moric, 2013)

Cluster Dynamics

Competitive Dynamics

Competitive pressure in the accommodation sector is perceived as low due to ongoing overcompensation of supply with demand in many regional destinations of the country, other tourism industries (operators) describe rising pressure

Composition and Competence in Networks

Cooperativeness and networking within and among the regions is underdeveloped from public and private side but slowly changing for the better

Tour operators deplore above all unfavorable infrastructural conditions and trade policy obstacles in air traffic as well as missing public regulation and coordination of prices among BRI partner countries

A limited ACAP of the tourism industry results in low levels of (mostly incremental) innovation activities. At the structural level, the clustering coefficients moderately indicate the presence of communities in the existing linkage network and sub-networks, which could be conducive for knowledge processing at the network level but the lack of hubs can have a detrimental effect

Entrepreneurial Orientation/

Capacity

At the firm level, corporate management structures (e. g. lack of knowledge management, centralized decision-making etc.) and corporate-cultures ((especially indications for high levels of In-Group Collectivism)) partially inhibit the development of ACAP, network consolidation and more radical innovation ventures. At the transnational level, the GLOBE-study points to certain cultural similarities which can serve as a baseline for future ACAP operating on the NSR as enabling infrastructure.

Moderating factors such as lack of competitive pressure and public sector support (in fields like human resource development, startup funding and network facilitation/institutionalization), bureaucratic burdens, regulatory costs and a deficient financial system have a negative conditioning effect here

In this respect, the findings from this study document that the NSR can provide a stimulus for the problems that hinder cluster maturation. However, developing this potential requires a concerted strategic framework to balance the maturation process within the tension field of cooperation and competition at multiple geographical levels (cmp. Moric, 2013; Gretzel et al., 2015), which is currently missing in Azerbaijan’s tourism policy. In order to prevent the maturation impulse from drying up in a number of individual, dissociated local initiatives, the opportunity must now be used to understand the existing destinations as integrated components of a national cluster system within a multi-level tourism ecosystem and to de-velop them accordingly. A major step along this way would be the systematic strengthening and linking of the regional DMCs to qualify and legitimize them as knowledge hubs or “neural systems” (Trunfio & Campana, 2019) in the (trans-)regional network structure based on a clear vision and marketing strategy that specify, among other things, target groups, (knowledge-) resources and themes to be developed and managed for the proposed routes. As the current debate on smart destinations shows (Gretzel et al., 2015), the creation of open (ICT-based) platforms within learning organizations and their enabling of hybrid, participatory forms of governance could serve as a major co-creative incentive for human and social capital building and thus innovation based cluster maturation within the tourism ecosystem (Roberts et al., 2012; Baggio et al., 2013; Isckia et al., 2018; Trunfio & Campana, 2019).

In this context, also existing industrial communities between tourism and related industries (including foreign tour operators) should be strategically developed. As traditional sectors in the DC such as agriculture, which is well connected with tourism in Azerbaijan, used to show higher levels of ACAP (Lejarraja & Walkenhorst, 2007) and tourism innovativeness use to heavily depend on knowledge absorption from related industries (Hjalager, 2010; Schuhbert, 2018), possibilities for a competence transfer should be explored here to sustain a maturation impulse in a cluster nucleus. Finally, the already observable change in private businesses towards an entrepreneurial orientation should be systematically supported (e. g. through start-up funding).

These measures could create the conditions for a comprehensive distribution of the NSR’s innovation potential along the cluster system and away from the BMA. ACAP can be increased within this framework so that not only incremental but increasingly radical innovations can be implemented to enrich the NSR with new products and services (cmp. Martinez-Roset al, 2009; Hjalager, 2010). Since the latter release more complementarities than incremental ones, this could allow for an increased stimulation of new linkages and the closure of structural gaps to a point where the system can start to mature on its own.

Up to this point, however, public institutions and policy makers will have to make enormous investments to prepare the system in time to catch up with the route projects that are already in progress. There is a substantial risk that if they do not manage to upgrade the conditions accordingly, a major share of control over the NSR’s potentials for a self-directed, regional economic diversification will be lost to transnational companies and investors (cmp. the phenomenon of (neo-)“colonization” that often occurs during the development stage of emerging tourism destinations in the DC; Vorlaufer, 1996; Letzner, 2010) or spatially misdirected to the BMA, therefore exacerbating the already existing spatial polarization of the Azerbaijani economy.To this end, the mixed methods presented here can be further developed into a toolkit for continuous monitoring and benchmarking (also with other NSR partner countries) in continuous coordination with indicator systems like the GCR or the upcoming 2020 Globe study, which is planned to cover Azerbaijan and other Caucasian countries for the first time.

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Footnotes

1

 These industries are known to be usually well-connected with tourism (cmp. Schuhbert, 2013).

2

 For the purpose of analysis, only the GLOBE study results on the level of national culture were selected, as the organizational culture overlaid with patterns of national culture (cmp. House et al., 2004).

3

 Multiple Linear Regression was applied for optimization under the aspect of collinearity, all coefficients given in Tab. 2 are significant at the .05 level

4

 Both measures build on 7-point Likert Scales

5

 Humane Orientation, on the other hand, or “the degree to which a collective encourages and rewards […] individuals for being fair, altruistic, generous, caring, and kind to others” is apparently detrimental to innovation.

6

 Trade, energy, agriculture and logistics are also stated here

7

 Culture-related start terms were derived from the original questionnaires of the 2004 GLOBE study.

8

 Other statements point to this local hiring policy and job creation as a source of pride in some companies.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • Andersson, T./Serger, S./Sörvik, J. & Wise, E. (2004): The Cluster Policies Whitebook. Malmö.

  • Arnegger, J. & Mayer, M. (2015): Azerbaijan’s Competitiveness as a Destination for International Tourists. Baku and Greifswald.

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  • Azernews (2019b): Azerbaijan’s co-op with China important for region – MP. Available online at https://www.azernews.az/news.php?news_id=157107&cat=nation, updated on 10/11/2019, checked on 12/21/2019.

  • Azernews (2019c): Azerbaijani MP: Transport projects begin to play key role in economy. Available online at https://www.azernews.az/news.php?news_id=158351&cat=nation, updated on 11/11/2019, checked on 12/21/2019.

  • Azernews (2019d): China Railway Express crosses Europe. Available online at https://www.azernews.az/news.php?news_id=158401&cat=business, updated on 11/12/2019, checked on 12/21/2019.

  • Azernews (2019e): China ready to cooperate to further simplify use of Trans-Caspian transport routes. Available online at https://www.azernews.az/news.php?news_id=152122& cat=business, updated on 6/13/2019, checked on 12/21/2019.

  • Baggio, R./Cooper, C. (2010): Knowledge transfer in a tourism destination – the effects of a network structure. In: The Service Industries Journal, 30(8).

  • Baggio R./Chiappa G.D. (2013): Tourism Destinations as Digital Business Ecosystems. In: Cantoni L., Xiang Z. (Eds.): Information and Communication Technologies in Tourism 2013. Springer, Berlin, Heidelberg.

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    Analytical Framework of the Study; level of reference: I = international, N= national, R = regional

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    Network of value creation processes of 81 Azerbaijani industries in 2011 based on “weighed degree”

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    GABEK Network of Associations on Key Category Terms