Enhancing Industrial Cluster Formation Through the Realistic Export Opportunities of the TRADE‐DSM

The article describes modern aspects of the basic instruments application of state-private partnership in the formation of the industrial cluster in the dairy industry. It is shown that the main range of tools of public-private partnership is well established in infrastructure projects. The feasibility of using these instruments for the dairy industry is dictated by the transition to the principles of import substitution (particularly in respect of dairy products). Characteristics of legal, organizational, economic and financial tools of public-private partnerships are used in the formation of dairy industrial cluster. Legal instruments are the adoption of an appropriate legislative framework (the agreement on the establishment of the cluster, Federal and regional target programs for the development of industrial clusters, the Concept of state support for territorial clusters in the period until 2018). The formation of industrial clusters is based on several laws in the Russian Federation such as: No. 224-FL "On state-private partnership, municipal-private partnership in the RF", Federal law №115-FL "On concession agreements" and laws of constituent entities of the Russian Federation on public-private partnerships (for example, from 01.06.2016 the law "On regulation of separate relations in the sphere of state-private partnership in the Voronezh region" No. 65-RL). The use of organizational and economic instruments aimed at choosing the optimal legal form that will operate the milk industry cluster (recommended non-profit partnership). It is shown that in modern conditions of market environment instability the financial instruments are of great importance, not only those which are widely distributed (e.g., blended funding), but new ones so called “pilot” tools. Such financial instruments, the author proposes to include, are the use of "deferred payments" and the use of scenario forecasting method. This method enables to carry out funds expenditure for the creation of the necessary infrastructure directly by the investor at the first stage. In this case at the next stage of industrial cluster development, expenses incurred by investor may be reimbursed (compensated) by entering in the budgets additional sources of income from the development of the territory of cluster functioning. The author's proposal is that in this case, in the accounts of the Investment Fund the financial resources for compensation of investors’ expenses can be accumulated to build the infrastructure of the cluster. The sources of additional revenues to the budget system may be additional amounts of tax paid by economic entities located on the territory of the dairy industry cluster, so we can talk about expanding the tax base caused by development of the territory. It is shown that in addition to using the tools of public-private partnership, formation of dairy industrial cluster must be done with consideration of foreign experience of functioning such clusters. The article is also attempted to highlight the main groups of risks that arise when implementing the investment project to build a dairy industrial cluster and to show the ways (tools) of the distribution of these risks between members of the cluster. The author has made the calculations for the change in funding between the major stakeholders in the dairy industrial cluster. In addition, the paper is concerned with a compensation model for the redistribution of additionally arising costs between the potential members of the dairy industrial cluster that would facilitate the use of the priority tools for the formation of dairy industrial cluster.

Service innovation drives economic growth and structural change by stimulating the development of new sectors and productivity improvements in existing sectors. Resource based sectors are the main contributors to South Africa’s North West province’s economic output This paper illustrates how such a region can use industrial cluster formation and focused export promotion as a strategy to enhance service innovation. Four service clusters were identified within the above mentioned province through structural path analysis and power of pull methods. An export market selection model is applied to the identified service industrial clusters to reveal realistic export opportunities associated with each cluster. Finally, trade multipliers are used to show the spill-over benefits given an increase in the clusters’ exports. Policymakers can use these results to inform actions that may assist in the development of these services clusters to strengthen the province’s competitive advantage and diversify its output.

This chapter investigates industrial clusters as building blocks of the Gauteng economy. As economic clusters are regarded as critical masses that are spatially concentrated, are somehow related, and impact one another as a result of their complementarities or similarities, such clusters reflect synergies between industries, suppliers and the public sector. The competitive advantages of such clusters are driven by agglomeration economies that ensure that firms benefit through availability of intermediate resources, relative lower costs of inputs, and increased multifactor productivity of management innovation, labour and capital inputs, for example. By applying principal component analysis to the Gauteng Social Accounting Matrix (GSAM), we identify six key industrial clusters for the Gauteng region. We further highlight inter-industry linkages within the dominant service clusters in the regional economy by means of a multiplicative decomposition model, the structural path analysis (SPA). These clusters are dominated by the Services and Trade cluster, which by itself, provided 68.5% of Gauteng’s regional employment, and contributed 55.9% to GVA, in 2015. These results will assist the relevant decision-makers in formulating and implementing appropriate strategies for economic growth and employment creation, leading to sustainable economic development in the Gauteng regional economy.

3Knowledge of a region’s comparative advantage may dictate its industrial development agenda and realistic export opportunities. Through the effective targeting of specific sectors and industries within the South African provinces, provincial government entities can determine which sector or industry could gain the most from effective targeting for industrial development, development planning and export promotion. This study determined the comparative advantage of South Africa’s Mpumalanga province by estimating the Revealed Comparative Advantage Index (RCA). The study revealed that the products with the highest comparative advantage (RCA) and realistic export opportunities (REO) are manganese products, salted meat (beef), frozen fish, chewing gum, tomatoes, soups and broths. In addition, the results of the RCA analysis were matched to the export opportunities identified by the decision support model (TRADE-DSM) to determine which of the comparative advantage products have realistic export opportunities. Eight of the top 15 comparative advantage products were found to have realistic export opportunities according to the TRADE-DSM.

Purpose– The purpose of this study was to explore the impact of the formation of industrial clusters on the obtainment of professional human resources, to verify the impact of human resources on clustering relationships and firm’s performance and to understand whether the formation of clusters can contribute to the obtainment of professional human resources and the improvement of competitiveness of enterprises. It was expected that solutions could be found to make new contributions through the verification of special economic zones (SEZs).Design/methodology/approach– Using manufacturers in Taiwan’s SEZs as the subjects, this study explored the impact on the obtainment of professional human resources after the formation of industrial clusters in SEZs, through conducting and empirical study with a questionnaire survey.Findings– The professional human resources are the essential factor for the formation of industrial clusters and the improvement of competitiveness. This study also confirmed that industries can have professional human resources by industrial clustering and that this will produce a positive impact on the enterprise clustering relationships, which can also have a positive impact on firm’s performance and can enhance the enterprise’s competitive advantage.Practical implications– Industrial clustering is the key factor to attract professional human resources; industrial clusters can enhance firm’s performance; and professional human resources affect firm’s performance of enterprises.Originality/value– No study has discussed the topic of clusters from the perspective of SEZs also including six export processing zone (EPZ) parks in Taiwan. This study discussed the topic using theories relating to clustering and human resources. The formation of industrial clusters can result in higher competitiveness in the face of the global market. The EPZ industrial cluster provides an excellent investment environment. Coupled with one-stop express services and geographic advantage, the land-use rate is up to 97 per cent and the per hectare output value amounts to NTD 3.2 billion, setting a successful example of an industrial cluster.

Industrial clusters provide ecological system for entrepreneurs to grow and the latter tend to agglomerate. However the influence of industrial cluster on entrepreneur's behavior in different stages of clusters is rarely studied. We argue the clusters can entrepreneurs' behavior in different stage of development of stage and entrepreneurs tend to agglomerate through learning mechanism. The relation of development stages of clusters and entrepreneurs' choice is discussed. Keywords-industrial clusters; entrepreneurship; formation With the rapid globalization and economic development, the location does not lose its role in development, instead industrial clusters (ICs) bosom around the world, such as innovation clusters in Silicon Valley in USA, software industrial clusters in Bangalore, India, Zhang Jiang High-tech Park in Shanghai, China etc. ICs are found in both developed countries and developing countries. They play important role in regional economy and have received the policy makers' attention around the world. However, the lack of understanding of dynamics of ICs can cause waste of resources and little achievement in term of economy in reality. The agglomeration of ICs is formed by the movement of workers through the pecuniary externalities (1). Learning plays an important role in mature clusters, and it can also affect the formation of industrial clusters in the early stage (2). Based on core-periphery model, it is assumed that the entrepreneurs' movement contributes to the formation of industrial cluster (3). We argue the entrepreneurs play a key role in the evolutionary process of ICs' development. Suppose a place where there is no entrepreneur before, and some entrepreneurs began their business by some random chance. Some successful entrepreneurs do their business well and accumulate capital, and then they become role model in the local area, which means some others will follow the suit and start the business. The local networks are formed and network density is becoming intense than other place through the external linkage. In order to understand the formation of industrial clusters, we should intentionally avoid the trial details, and that allows us to grasp the general principle of tendency of agglomeration. Concerning about the life cycle of industry, it can affect the entrepreneur and the evolutionary process significantly. However, the existing formation models notably neglect the interaction among them, such as the inter-relation between development stages of ICs and entrepreneurs' behavior. In this article we absorb the industry life cycle theory, industrial clusters theory, evolutionary theory and entrepreneurship theory to deal with the formation of industrial cluster. Particularly, in this paper, entrepreneurship is fully considered and proved by a visualized simulation model to identify its role in the formation cluster. Further discussion about the relation of the ICs' development stages and entrepreneurs' behavior is in the last part of the essay.

PurposeThis paper aims to identify Thailand’s realistic export opportunities (REOs) in the ASEAN+3 countries (i.e. ASEAN, Greater China, Japan and South Korea), which together constitute an economically dynamic region and a strategic export destination for Thailand. Furthermore, the paper seeks to determine the extent to which Thailand already has a share in ASEAN+3 countries and where new opportunities lie. This allows the formulation of appropriate export promotion strategies for Thailand.Design/methodology/approachThe methodology used is a decision support model (DSM) which uses an extensive data-filtering system to systematically screen and eliminate less-promising product–country combinations to ultimately reveal high-potential REOs. Product–country combinations are screened on the basis of country risk; macro-economic country performance; market potential in terms of import growth and import market size; and market access conditions, including market concentration and the existence of trade barriers. The thus narrowed-down REOs are categorised according to Thailand’s relative market share in, and the characteristics of, the identified import markets.FindingsThe study reveals that the ASEAN+3 countries account for about 40 per cent of the total potential export value of Thailand’s REOs in the world, with China leading the way (12.45 per cent), followed by Japan (8.56 per cent) and South Korea (6.23 per cent). However, Thailand has a relatively small or intermediately small market share in the majority of these REOs, pointing to the need for more offensive and exploratory export promotion strategies.Research limitations/implicationsThe ASEAN+3 countries – given that they are an abundant source of REOs for Thailand and are in Thailand’s “backyard” – should receive more focused attention and resources in government export promotion efforts. The recent launch of the ASEAN Economic Community and the proposed establishment of an East Asia Free Trade Area lend weight to the idea of Thailand adopting a strong regional focus in its export activities.Practical implicationsThe insights derived from the study are valuable for export promotion officials, industry representatives and practising exporters alike, as they constitute an easy-to-digest snapshot of high-potential REOs for Thailand in the ASEAN+3 region. This makes for more efficient planning and prioritising of export development activities, and a more streamlined approach to resource allocation.Originality/valueExport promotion shows diminishing returns and requires sustainable strategies and interventions. The value in this paper lies in its description of an innovative market selection tool, the DSM, which is able to process and filter high volumes of information and arrive at a shortlist of high-potential REOs for Thailand in the ASEAN+3 countries. The paper represents a concise case study of the DSM in practice, which should be of particular interest to export promotion agencies, industry associations and both new and more established exporting countries.

Drawing on the framework of spatial economics, this chapter presents a microeconomic framework for understanding the formation and growth of economic agglomerations and industrial clusters. Spatial economics, a field created in the early 1990s, represents a new branch of economics that aims to explain the formation and growth of various forms of economic agglomeration in geographical space, using a general equilibrium framework combined with an evolutionary approach. Spatial economics is often called “the new economic geography,” and the two terms are often used interchangeably throughout this chapter.1 Although the chapter’s main focus is on the theory used to explain industrial agglomerations and clusters, we also consider the difference between various forms or types of economic agglomerations. Given that most industrial agglomerations in the real world are embedded in a larger agglomeration such as a city or a region, a broader viewpoint is helpful to achieve a comprehensive understanding of the formation and growth of a specific industrial agglomeration or cluster.KeywordsTransport CostInnovation ActivityTrade CostEconomic GeographyIndustrial DistrictThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

With the rapid development of global economy, the industrial cluster has become the new trend of world economic development. So far, the industrial cluster mode with space as the main division has been formed. The cooperation of industrial clusters is dynamic. The industries in the cluster cooperate with each other for mutual benefit and win-win, occupying a place in the fierce market competition. In addition, the industrial cluster is also conducive to strengthen the international economic division of labor and points out the direction of regional industrial transfer. China is now in a critical period of economic development; the industrial cluster plays an important role in China's industrial transformation and economic development. At present, the most common regional development mode in China is industrial cluster. The emergence of industrial cluster accelerates the development of industrial regional economy and the balance of industrial layout. Industrial clusters occupy a key position in China's economic industry chain, and the development and change in industrial clusters will directly affect the development of the entire industrial chain. This study first simulates the evolution path of industrial cluster and then establishes the relevant data model. Finally, through repast simulation, it puts forward conclusions and suggestions according to the verification results. The construction of dynamic model can realize the simulation of industrial cluster theory. According to the simulation results, we can find that the ecosystem in different stages will produce different characteristics; the formation and evolution of industrial clusters are actually the epitome of market development. In this process, the government guidance and market regulation are needed to accelerate the formation of industrial cluster ecosystem and increase the scale of industrial cluster.

Purpose This paper aims to identify China’s realistic export opportunities (REOs) among the “Belt and Road Initiative” (BRI) group of countries. Design/methodology/approach The methodology used is a decision support model (DSM) that filters data based on country risk; macro-economic country performance; market potential in terms of import growth and import market size; and market access conditions. The high-potential REOs are revealed. Findings Out of the 84 BRI countries, 79 countries represent 42.5% of China’s REOs globally and 26.9% of China’s globally untapped potential value. Interestingly, 17.9% of this untapped potential is in the BRI countries Poland, Austria and the Czech Republic, thus providing a potentially important route into the European Union. Research limitations/implications If China wants to develop additional or new markets, focus should be put on the BRI markets outside of the top 20. China should also invest in the development of most BRI economies, to ensure their future growth and increased demand for import of products and services from China. Practical implications The shortlist of China’s REOs in the individual BRI countries makes for more efficient planning and prioritising of export development activities. It also highlights the need for policymakers to look beyond international trade and focus on how to also improve the domestic economies of the BRI partners. Originality/value To the best of authors’ knowledge, this paper is the first to use the DSM to identify China’s REOs at HS6-digit level within the BRI group. The findings have important implications for China’s export promotion agencies, industry associations and individual companies.

The purpose of the study is to develop a methodological apparatus for the formation of dual-use scientific and industrial clusters—a form recognized at the highest level of management of the military-industrial complex to help diversify defense enterprises and organizations. Based on the results of the work, the following main conclusions were obtained. The few dual-use scientific and industrial clusters created in recent years are still not much different from the well-known vary-ants of the organization of industrial and innovative clusters and it is not entirely clear how they will fulfill their main purpose—to facilitate the transfer of defense technologies to the civilian sector. First of all, this concerns the issues of removing the regime of secrecy from military technologies that can be used to produce civilian products. Experts call this problem the main obstacle to the transfer of such technologies. At the same time, starting in 2022, the list of dual-use goods and technologies that can be used in the creation of weapons and military equipment and for which export control is carried out is approved and updated. This list contains unambiguous exceptions allowing the use of dual-use goods and technologies for civilian purposes. The second problem—the choice of an anchor company for the cluster—is being addressed ambiguously today. The article shows that the most forest-like solution is the formation of a cluster around a reputable scientific and industrial company in the field of cluster specialization. Given the competitive nature of the activities of defense organizations in the civilian market, it is also necessary to provide options for organizing relations between its developers and manufacturers. The article describes organizational solutions of this plan, involving the creation of consortia, joint ventures, as well as the release of products within the framework of contract production and franchise.

Agglomeration economies, including economies of scale, better employee–employer matching and supplier–buyer matching, and knowledge spillovers, play a key role in the formation of large cities and industrial clusters. This chapter introduces models of economic geography that explain the process of agglomeration and formation of industrial clusters. These models describe how the reduction of transportation costs and development of labour productivity affect the formation of industrial clusters. Then we discuss important issues in empirical analysis, such as selection bias, sample selection bias, relocation effects, and external validity. Finally empirical studies on agglomeration economies, and the effects of industrial zones and infrastructure improvement, are reviewed. Empirical results of the effectiveness of industrial zones and infrastructure improvement are mixed, suggesting the importance of careful diagnosis of the economic conditions and an understanding of economic structure for choosing appropriate policies and interventions.

Article history: Received March 26, 2012 Accepted 15 June 2012 Available online June 16 2012 Tendency to industrial clustering at the end of the twentieth century was a turning point in industrial development programs in most countries of the world. Industrial clustering is a model of industrial organization, which has entered industrial literature as a new development strategy. Clustering has provided utilization of efficiencies of scale and aggregation as well as efficiencies of collective efforts by creating conditions for competitiveness advantage, economical growth and export development in the international environment. Today, industrial clustering has been considered as a fundamental strategy for economic development and growth in almost all countries of the world including Iran. This paper aims to assess and to explain important factors affecting the competitiveness of industrial clusters. It also shows the relationship among these factors together. The proposed study uses fuzzy DEMATEL technique; hence, the affecting factors of competitiveness of industrial clusters in the automotive cluster in one of the provinces of Iran is investigated and the importance of each of these factors and their relationships are identified. © 2012 Growing Science Ltd. All rights reserved.

Economic modelling techniques can assist policy makers to understand the effects of policy or external shocks and to make informed decisions about economic development programmes. Economic diversification is a priority of resource-dependent regions such as South Africas North West Province (NWP) in the wake of the 2014 platinum strike. The economy of the NWP is highly specialised and dependent on a few sectors - in particular, mining and quarrying. Both the NWP and the South African economies were adversely affected by a prolonged strike in the platinum sector.This paper sets out to illustrate the effects of industrial cluster formation as a strategy to enhance competitiveness in the NWP and diversify its economy using SAM multiplier analysis. The supported activity of eight of the ten industrial clusters was shown to be greater than the actual activity, indicating that industrial cluster formation will enhance economic activity in the NWP. Of the ten identified clusters for the NWP, four were found to be moderately integrated and to have high upstream effects. Finally, structural change in the NWP economy through industrial cluster formation was observed using economic landscaping. A key finding was that the identified industrial clusters are significant contributors to the structural change of the NWP economic landscape with the promotion of cluster-specific exports. It is recommended that the North West provincial government adopt this strategy with a view to enhancing competitiveness and economic diversification.

The creation and development of industrial clusters is one of the tools for the development of industry, both regions and Russia as a whole. Industrial clusters create conditions for the advanced development of Russian industry. The formation of regional industry clusters is the most important stage in the creation of an innovative economy. The modernization of the industrial complex, the creation of new industrial regional clusters and clusters on an interregional basis will allow the region's economy to develop. This will ensure the growth of the share of high-tech industrial products of the Voronezh region in the overall structure of production in the national market. The effectiveness of the cluster approach is that it allows you to form a comprehensive view of the state policy of development of the region by supporting not just groups of enterprises and individual industries, and effective long-term relationships between them. In this regard, this paper describes the experience of the cluster approach to the development of industry in the region (on the example of the Voronezh region).